From f9cea93645167ed22fc98854b4c1a7a27031ab01 Mon Sep 17 00:00:00 2001 From: dnth Date: Wed, 19 Jul 2023 13:14:10 +0800 Subject: [PATCH 1/6] rerun --- examples/video-yolov5-detection.ipynb | 9409 ++++--------------------- 1 file changed, 1464 insertions(+), 7945 deletions(-) diff --git a/examples/video-yolov5-detection.ipynb b/examples/video-yolov5-detection.ipynb index 844a3ba0..238aa9ec 100644 --- a/examples/video-yolov5-detection.ipynb +++ b/examples/video-yolov5-detection.ipynb @@ -31,36 +31,29 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 11, "id": "1fb73f7e-1bd9-4e8e-b113-94a714abca73", "metadata": {}, "outputs": [], "source": [ - "!pip install fastdup gdown -Uq" + "!pip install fastdup kaggle -Uq" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 12, "id": "90d6aea7-f03e-4a9c-ba2c-dee490579304", "metadata": { "tags": [] }, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/usr/bin/dpkg\n" - ] - }, { "data": { "text/plain": [ - "'1.25'" + "'1.27'" ] }, - "execution_count": 2, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -80,62 +73,1037 @@ }, { "cell_type": "code", - "execution_count": 3, - "id": "a9525826-b454-43e4-a359-969e44335861", - "metadata": { - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Downloading...\n", - "From (uriginal): https://drive.google.com/uc?id=1fzmOgmRu557aU4lEbzL7XCf78KntFCeQ\n", - "From (redirected): https://drive.google.com/uc?id=1fzmOgmRu557aU4lEbzL7XCf78KntFCeQ&confirm=t&uuid=3d1e9ae0-b405-404f-a0ed-9174b2401633\n", - "To: /media/dnth/Active-Projects/fastdup/examples/data.zip\n", - "100%|██████████████████████████████████████| 56.9M/56.9M [00:05<00:00, 10.5MB/s]\n" - ] - } - ], + "execution_count": null, + "id": "e9fd45b0", + "metadata": {}, + "outputs": [], "source": [ - "!gdown --fuzzy https://drive.google.com/file/d/1fzmOgmRu557aU4lEbzL7XCf78KntFCeQ/view" + "!kaggle datasets download -d erikvdven/tiktok-trending-december-2020" ] }, { "cell_type": "code", - "execution_count": 4, - "id": "02650635-fb41-47f5-bd5c-ea78e8c80b15", + "execution_count": 13, + "id": "2e0674a5", "metadata": { - "tags": [] + "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Archive: data.zip\n", - " creating: data/\n", - " inflating: data/video_14.mp4 \n", - " inflating: data/video_13.mp4 \n", - " inflating: data/video_12.mp4 \n", - " inflating: data/video_9.mp4 \n", - " inflating: data/video_15.mp4 \n", - " inflating: data/video_10.mp4 \n", - " inflating: data/video_11.mp4 \n", - " inflating: data/video_8.mp4 \n", - " inflating: data/video_1.mp4 \n", - " inflating: data/video_2.mp4 \n", - " inflating: data/video_3.mp4 \n", - " inflating: data/video_4.mp4 \n", - " inflating: data/video_5.mp4 \n", - " inflating: data/video_6.mp4 \n", - " inflating: data/video_7.mp4 \n" + "Archive: tiktok-trending-december-2020.zip\n", + " inflating: 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"execution_count": 5, + "execution_count": 14, "id": "9258e5af-0802-476b-85ba-2423240a2771", "metadata": { "tags": [] @@ -163,8 +1131,8 @@ "output_type": "stream", "text": [ "FastDup Software, (C) copyright 2022 Dr. Amir Alush and Dr. Danny Bickson.\n", - "2023-07-12 16:11:02 [INFO] Going to loop over dir data\n", - "2023-07-12 16:11:02 [INFO] Found total 15 videos to run on, 15 train, 0 test, name list 15, counter 15 \n" + "2023-07-19 13:06:39 [INFO] Going to loop over dir data\n", + "2023-07-19 13:06:39 [INFO] Found total 1000 videos to run on, 1000 train, 0 test, name list 1000, counter 1000 \n" ] }, { @@ -173,13 +1141,13 @@ "0" ] }, - "execution_count": 5, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "fastdup.extract_video_frames(input_dir=\"data\", work_dir=\"frames\")" + "fastdup.extract_video_frames(input_dir=\"data/\", work_dir=\"frames/\")" ] }, { @@ -194,19 +1162,27 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 15, "id": "bd3bf19f-1322-46cc-bfc3-d8db50689367", "metadata": { "tags": [] }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Warning: fastdup create() without work_dir argument, output is stored in a folder named work_dir in your current working path.\n" + ] + } + ], "source": [ - "fd = fastdup.create(input_dir='frames', work_dir='yolov5_detection_work_dir')" + "fd = fastdup.create(input_dir='frames/')" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 16, "id": "29fde366-db7d-4fff-a537-2ff589cddffd", "metadata": { "tags": [] @@ -216,39 +1192,38 @@ "name": "stdout", "output_type": "stream", "text": [ - "Trying to download yolov5s model from https://github.com/itsnine/yolov5-onnxruntime/raw/master/models/yolov5s.onnx\n", "FastDup Software, (C) copyright 2022 Dr. Amir Alush and Dr. Danny Bickson.\n", - "2023-07-12 16:11:11 [INFO] Going to loop over dir frames\n", - "2023-07-12 16:11:11 [INFO] Found total 99 images to run on, 99 train, 0 test, name list 99, counter 99 \n", + "2023-07-19 13:07:01 [INFO] Going to loop over dir frames\n", + "2023-07-19 13:07:01 [INFO] Found total 1000 images to run on, 1000 train, 0 test, name list 1000, counter 1000 \n", "FastDup Software, (C) copyright 2022 Dr. Amir Alush and Dr. Danny Bickson.utes\n", - "2023-07-12 16:11:22 [INFO] Going to loop over dir /tmp/crops_input.csv\n", - "2023-07-12 16:11:22 [INFO] Found total 130 images to run on, 130 train, 0 test, name list 130, counter 130 \n", - "2023-07-12 16:11:23 [INFO] Found total 130 images to run onstimated: 0 Minutes\n", - "Finished histogram 0.156\n", - "Finished bucket sort 0.168\n", - "2023-07-12 16:11:23 [INFO] 10) Finished write_index() NN model\n", - "2023-07-12 16:11:23 [INFO] Stored nn model index file yolov5_detection_work_dir/nnf.index\n", - "2023-07-12 16:11:23 [INFO] Total time took 1016 ms\n", - "2023-07-12 16:11:23 [INFO] Found a total of 0 fully identical images (d>0.990), which are 0.00 %\n", - "2023-07-12 16:11:23 [INFO] Found a total of 6 nearly identical images(d>0.980), which are 2.31 %\n", - "2023-07-12 16:11:23 [INFO] Found a total of 65 above threshold images (d>0.900), which are 25.00 %\n", - "2023-07-12 16:11:23 [INFO] Found a total of 13 outlier images (d<0.050), which are 5.00 %\n", - "2023-07-12 16:11:23 [INFO] Min distance found 0.555 max distance 0.988\n", - "2023-07-12 16:11:23 [INFO] Running connected components for ccthreshold 0.960000 \n", + "2023-07-19 13:08:57 [INFO] Going to loop over dir /tmp/crops_input.csv\n", + "2023-07-19 13:08:57 [INFO] Found total 1000 images to run on, 1000 train, 0 test, name list 1000, counter 1000 \n", + "2023-07-19 13:09:00 [INFO] Found total 1000 images to run ontimated: 0 Minutes\n", + "Finished histogram 0.220\n", + "Finished bucket sort 0.427\n", + "2023-07-19 13:09:00 [INFO] 20) Finished write_index() NN model\n", + "2023-07-19 13:09:00 [INFO] Stored nn model index file work_dir/nnf.index\n", + "2023-07-19 13:09:00 [INFO] Total time took 3035 ms\n", + "2023-07-19 13:09:00 [INFO] Found a total of 2 fully identical images (d>0.990), which are 0.10 %\n", + "2023-07-19 13:09:00 [INFO] Found a total of 12 nearly identical images(d>0.980), which are 0.60 %\n", + "2023-07-19 13:09:00 [INFO] Found a total of 394 above threshold images (d>0.900), which are 19.70 %\n", + "2023-07-19 13:09:00 [INFO] Found a total of 100 outlier images (d<0.050), which are 5.00 %\n", + "2023-07-19 13:09:00 [INFO] Min distance found 0.446 max distance 0.991\n", + "2023-07-19 13:09:00 [INFO] Running connected components for ccthreshold 0.960000 \n", ".0\n", " ########################################################################################\n", "\n", "Dataset Analysis Summary: \n", "\n", - " Dataset contains 130 images\n", - " Valid images are 100.00% (130) of the data, invalid are 0.00% (0) of the data\n", - " Similarity: 4.62% (6) belong to 2 similarity clusters (components).\n", - " 95.38% (124) images do not belong to any similarity cluster.\n", - " Largest cluster has 30 (23.08%) images.\n", + " Dataset contains 1000 images\n", + " Valid images are 100.00% (1,000) of the data, invalid are 0.00% (0) of the data\n", + " Similarity: 2.40% (24) belong to 4 similarity clusters (components).\n", + " 97.60% (976) images do not belong to any similarity cluster.\n", + " Largest cluster has 16 (1.60%) images.\n", " For a detailed analysis, use `.connected_components()`\n", "(similarity threshold used is 0.9, connected component threshold used is 0.96).\n", "\n", - " Outliers: 8.46% (11) of images are possible outliers, and fall in the bottom 5.00% of similarity values.\n", + " Outliers: 6.40% (64) of images are possible outliers, and fall in the bottom 5.00% of similarity values.\n", " For a detailed list of outliers, use `.outliers()`.\n" ] }, @@ -258,13 +1233,13 @@ "0" ] }, - "execution_count": 7, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "fd.run(bounding_box='yolov5s')" + "fd.run(bounding_box='yolov5s', num_images=1000)" ] }, { @@ -279,697 +1254,15 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 18, "id": "c13076de-3cf2-428f-866f-24278b082c02", "metadata": { + "scrolled": false, "tags": [] }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 37.14it/s]\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Finished OK. Components are stored as image files yolov5_detection_work_dir/galleries/components_[index].jpg\n", - "Stored components visual view in yolov5_detection_work_dir/galleries/components.html\n", - "Execution time in seconds 0.1\n" - ] - }, - { - "data": { - "text/html": [ - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " Components Report\n", - " \n", - " \n", - "\n", - "\n", - "\n", - "
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Components Report

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component84
num_images8
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person8
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laptop2
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component40
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person2
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Info From
from/crops/tmpdatavideo_10.mp4output_000006.jpg_-6_166_579_856.jpg
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Info To
0.919327/crops/tmpdatavideo_10.mp4output_000005.jpg_-2_202_558_824.jpg
0.910453/crops/tmpdatavideo_10.mp4output_000001.jpg_8_214_542_808.jpg
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Info From
from/crops/tmpdatavideo_10.mp4output_000001.jpg_8_214_542_808.jpg
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Info To
0.943799/crops/tmpdatavideo_10.mp4output_000005.jpg_-2_202_558_824.jpg
0.910453/crops/tmpdatavideo_10.mp4output_000006.jpg_-6_166_579_856.jpg
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Info From
from/crops/tmpdatavideo_14.mp4output_000002.jpg_331_403_226_472.jpg
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Info To
0.91401/crops/tmpdatavideo_14.mp4output_000001.jpg_368_378_186_478.jpg
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Info From
from/crops/tmpdatavideo_14.mp4output_000001.jpg_368_378_186_478.jpg
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0.91401/crops/tmpdatavideo_14.mp4output_000002.jpg_331_403_226_472.jpg
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Info From
from/crops/tmpdatavideo_6.mp4output_000003.jpg_2_13_560_995.jpg
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0.919047/crops/tmpdatavideo_6.mp4output_000005.jpg_21_32_557_1000.jpg
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Info From
from/crops/tmpdatavideo_6.mp4output_000005.jpg_21_32_557_1000.jpg
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Info To
0.921029/crops/tmpdatavideo_6.mp4output_000007.jpg_2_22_549_957.jpg
0.919047/crops/tmpdatavideo_6.mp4output_000003.jpg_2_13_560_995.jpg
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Info From
from/crops/tmpdatavideo_10.mp4output_000005.jpg_-2_202_558_824.jpg
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Info To
0.943799/crops/tmpdatavideo_10.mp4output_000001.jpg_8_214_542_808.jpg
0.919327/crops/tmpdatavideo_10.mp4output_000006.jpg_-6_166_579_856.jpg
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Info From
from/crops/tmpdatavideo_6.mp4output_000007.jpg_2_22_549_957.jpg
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0.921029/crops/tmpdatavideo_6.mp4output_000005.jpg_21_32_557_1000.jpg
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from/crops/tmpdatavideo_1.mp4output_000010.jpg_10_134_714_1128.jpg
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0.921314/crops/tmpdatavideo_1.mp4output_000011.jpg_20_70_702_1192.jpg
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The dataset consists of the first 1000 trending videos scraped from TikTok on December 2020.\n", + "\n", + "You can download the dataset by manually by heading to the dataset [homepage](https://www.kaggle.com/datasets/erikvdven/tiktok-trending-december-2020) or using the [Kaggle API](https://github.com/Kaggle/kaggle-api). \n", + "\n", + "Let's use the Kaggle API to download the dataset:" ] }, { @@ -81,1029 +95,24 @@ "!kaggle datasets download -d erikvdven/tiktok-trending-december-2020" ] }, + { + "cell_type": "markdown", + "id": "f21725cb", + "metadata": {}, + "source": [ + "Next, extract the .zip file into a folder named `data`." + ] + }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 3, "id": "2e0674a5", "metadata": { "scrolled": true }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Archive: tiktok-trending-december-2020.zip\n", - " inflating: data/audd/audd_music.csv \n", - " inflating: data/audd/audd_music_apple_music.csv \n", - 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"2023-07-19 13:06:39 [INFO] Going to loop over dir data\n", - "2023-07-19 13:06:39 [INFO] Found total 1000 videos to run on, 1000 train, 0 test, name list 1000, counter 1000 \n" + "2023-07-19 13:17:39 [INFO] Going to loop over dir data\n", + "2023-07-19 13:17:39 [INFO] Found total 1000 videos to run on, 1000 train, 0 test, name list 1000, counter 1000 \n" ] }, { @@ -1141,7 +150,7 @@ "0" ] }, - "execution_count": 14, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -1162,7 +171,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 5, "id": "bd3bf19f-1322-46cc-bfc3-d8db50689367", "metadata": { "tags": [] @@ -1180,9 +189,17 @@ "fd = fastdup.create(input_dir='frames/')" ] }, + { + "cell_type": "markdown", + "id": "737ae835", + "metadata": {}, + "source": [ + "For demonstration we'll just run on `num_images=2000`, feel free to change its value or omitting it altogether to run it on the entire dataset." + ] + }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 6, "id": "29fde366-db7d-4fff-a537-2ff589cddffd", "metadata": { "tags": [] @@ -1193,37 +210,37 @@ "output_type": "stream", "text": [ "FastDup Software, (C) copyright 2022 Dr. Amir Alush and Dr. Danny Bickson.\n", - "2023-07-19 13:07:01 [INFO] Going to loop over dir frames\n", - "2023-07-19 13:07:01 [INFO] Found total 1000 images to run on, 1000 train, 0 test, name list 1000, counter 1000 \n", + "2023-07-19 13:18:11 [INFO] Going to loop over dir frames\n", + "2023-07-19 13:18:11 [INFO] Found total 2000 images to run on, 2000 train, 0 test, name list 2000, counter 2000 \n", "FastDup Software, (C) copyright 2022 Dr. Amir Alush and Dr. Danny Bickson.utes\n", - "2023-07-19 13:08:57 [INFO] Going to loop over dir /tmp/crops_input.csv\n", - "2023-07-19 13:08:57 [INFO] Found total 1000 images to run on, 1000 train, 0 test, name list 1000, counter 1000 \n", - "2023-07-19 13:09:00 [INFO] Found total 1000 images to run ontimated: 0 Minutes\n", - "Finished histogram 0.220\n", - "Finished bucket sort 0.427\n", - "2023-07-19 13:09:00 [INFO] 20) Finished write_index() NN model\n", - "2023-07-19 13:09:00 [INFO] Stored nn model index file work_dir/nnf.index\n", - "2023-07-19 13:09:00 [INFO] Total time took 3035 ms\n", - "2023-07-19 13:09:00 [INFO] Found a total of 2 fully identical images (d>0.990), which are 0.10 %\n", - "2023-07-19 13:09:00 [INFO] Found a total of 12 nearly identical images(d>0.980), which are 0.60 %\n", - "2023-07-19 13:09:00 [INFO] Found a total of 394 above threshold images (d>0.900), which are 19.70 %\n", - "2023-07-19 13:09:00 [INFO] Found a total of 100 outlier images (d<0.050), which are 5.00 %\n", - "2023-07-19 13:09:00 [INFO] Min distance found 0.446 max distance 0.991\n", - "2023-07-19 13:09:00 [INFO] Running connected components for ccthreshold 0.960000 \n", + "2023-07-19 13:21:54 [INFO] Going to loop over dir /tmp/crops_input.csv\n", + "2023-07-19 13:21:54 [INFO] Found total 2000 images to run on, 2000 train, 0 test, name list 2000, counter 2000 \n", + "2023-07-19 13:21:59 [INFO] Found total 2000 images to run ontimated: 0 Minutes\n", + "Finished histogram 0.400\n", + "Finished bucket sort 0.409\n", + "2023-07-19 13:21:59 [INFO] 36) Finished write_index() NN model\n", + "2023-07-19 13:21:59 [INFO] Stored nn model index file work_dir/nnf.index\n", + "2023-07-19 13:21:59 [INFO] Total time took 5078 ms\n", + "2023-07-19 13:21:59 [INFO] Found a total of 6 fully identical images (d>0.990), which are 0.15 %\n", + "2023-07-19 13:21:59 [INFO] Found a total of 47 nearly identical images(d>0.980), which are 1.18 %\n", + "2023-07-19 13:21:59 [INFO] Found a total of 844 above threshold images (d>0.900), which are 21.10 %\n", + "2023-07-19 13:21:59 [INFO] Found a total of 200 outlier images (d<0.050), which are 5.00 %\n", + "2023-07-19 13:21:59 [INFO] Min distance found 0.523 max distance 0.995\n", + "2023-07-19 13:21:59 [INFO] Running connected components for ccthreshold 0.960000 \n", ".0\n", " ########################################################################################\n", "\n", "Dataset Analysis Summary: \n", "\n", - " Dataset contains 1000 images\n", - " Valid images are 100.00% (1,000) of the data, invalid are 0.00% (0) of the data\n", - " Similarity: 2.40% (24) belong to 4 similarity clusters (components).\n", - " 97.60% (976) images do not belong to any similarity cluster.\n", - " Largest cluster has 16 (1.60%) images.\n", + " Dataset contains 2000 images\n", + " Valid images are 100.00% (2,000) of the data, invalid are 0.00% (0) of the data\n", + " Similarity: 3.45% (69) belong to 10 similarity clusters (components).\n", + " 96.55% (1,931) images do not belong to any similarity cluster.\n", + " Largest cluster has 28 (1.40%) images.\n", " For a detailed analysis, use `.connected_components()`\n", "(similarity threshold used is 0.9, connected component threshold used is 0.96).\n", "\n", - " Outliers: 6.40% (64) of images are possible outliers, and fall in the bottom 5.00% of similarity values.\n", + " Outliers: 6.90% (138) of images are possible outliers, and fall in the bottom 5.00% of similarity values.\n", " For a detailed list of outliers, use `.outliers()`.\n" ] }, @@ -1233,13 +250,13 @@ "0" ] }, - "execution_count": 16, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "fd.run(bounding_box='yolov5s', num_images=1000)" + "fd.run(bounding_box='yolov5s', num_images=2000)" ] }, { @@ -1254,7 +271,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 7, "id": "c13076de-3cf2-428f-866f-24278b082c02", "metadata": { "scrolled": false, @@ -1275,7 +292,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 8, "id": "3edfd955-da16-455d-9089-87ee06161d9c", "metadata": { "scrolled": false, @@ -1286,7 +303,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 20/20 [00:00<00:00, 99.01it/s]\n" + "100%|██████████████████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 80.17it/s]\n" ] }, { @@ -1295,16 +312,1103 @@ "text": [ "Finished OK. Components are stored as image files work_dir/galleries/components_[index].jpg\n", "Stored components visual view in work_dir/galleries/components.html\n", - "Execution time in seconds 0.4\n" + "Execution time in seconds 0.5\n" ] }, + { + "data": { + "text/html": [ + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " Components Report\n", + " \n", + " \n", + "\n", + "\n", + "\n", + "
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Components Report

Showing groups of similar images

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component1703
num_images2
mean_distance0.9736
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component1749
num_images2
mean_distance0.9693
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Similarity Report

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0.910023/crops/tmpdatavideos6880848041792802053.mp4output_000001.jpg_205_427_43_56.jpg
0.901012/crops/tmpdatavideos6880848041792802053.mp4output_000006.jpg_347_373_98_112.jpg
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from/crops/tmpdatavideos6880694458552175874.mp4output_000006.jpg_80_60_55_133.jpg
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0.912736/crops/tmpdatavideos6880694458552175874.mp4output_000005.jpg_79_54_52_135.jpg
0.901303/crops/tmpdatavideos6880694458552175874.mp4output_000005.jpg_108_65_45_107.jpg
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0.909584/crops/tmpdatavideos6880848041792802053.mp4output_000010.jpg_258_402_43_50.jpg
0.901421/crops/tmpdatavideos6880848041792802053.mp4output_000003.jpg_234_384_48_59.jpg
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11work_dir/crops/framestmpdatavideos6875394675985992966.mp4output_000001.jpg_376_210_33_95.jpgframes/tmp/datavideos6875394675985992966.mp4/output_000001.jpgVALIDTrue
22work_dir/crops/framestmpdatavideos6875394675985992966.mp4output_000001.jpg_555_223_45_101.jpgframes/tmp/datavideos6875394675985992966.mp4/output_000001.jpgVALIDTrue
33work_dir/crops/framestmpdatavideos6875394675985992966.mp4output_000001.jpg_461_215_22_53.jpgframes/tmp/datavideos6875394675985992966.mp4/output_000001.jpgVALIDTrue
44work_dir/crops/framestmpdatavideos6875394675985992966.mp4output_000001.jpg_428_211_33_52.jpgframes/tmp/datavideos6875394675985992966.mp4/output_000001.jpgVALIDTrue
..................
995995work_dir/crops/framestmpdatavideos6880161721349311746.mp4output_000001.jpg_3_370_570_658.jpgframes/tmp/datavideos6880161721349311746.mp4/output_000001.jpgVALIDTrue
996996work_dir/crops/framestmpdatavideos6880196605513927938.mp4output_000002.jpg_155_501_78_222.jpgframes/tmp/datavideos6880196605513927938.mp4/output_000002.jpgVALIDTrue
997997work_dir/crops/framestmpdatavideos6880196605513927938.mp4output_000002.jpg_262_278_310_736.jpgframes/tmp/datavideos6880196605513927938.mp4/output_000002.jpgVALIDTrue
998998work_dir/crops/framestmpdatavideos6880196605513927938.mp4output_000002.jpg_293_350_109_120.jpgframes/tmp/datavideos6880196605513927938.mp4/output_000002.jpgVALIDTrue
999999work_dir/crops/framestmpdatavideos6880196605513927938.mp4output_000002.jpg_248_358_66_94.jpgframes/tmp/datavideos6880196605513927938.mp4/output_000002.jpgVALIDTrue
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Bright Image Report

Showing example images, sort by descending order

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+ " display: flex;\n", + " flex-direction: row;\n", + " justify-content: flex-start;\n", + " align-items: stretch;\n", + " flex-wrap: nowrap;\n", + " \n", + "}\n", + ".table-row:nth-child(2) td {\n", + " border-top: none;\n", + "}\n", + ".table-row:nth-child(2n + 1) {\n", + " /* background: #2e282a33; */\n", + "}\n", + ".table-row:last-child td:first-child {\n", + " border-bottom-left-radius: 10px;\n", + " width: 10%;\n", + " flex-grow: 1;\n", + " flex-shrink: 0;\n", + " font-weight: 600;\n", + " font-size: 1.4rem;\n", + " line-height: 0.9285714286;\n", + " color: #2E3E8E;\n", + "border: none;\n", + "\n", + " padding: 15px 14px;\n", + " border-spacing: 0;\n", + " word-wrap: break-word;\n", + " height: auto;\n", + " border-color: #657BEC;\n", + " text-align: center !important;\n", + " border-radius-top: 10px;\n", + "}\n", + ".table-row:last-child td:last-child {\n", + " border-bottom-right-radius: 10px;\n", + "}\n", + ".table th {\n", + " width: 100%;\n", + " border-top-left-radius: 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sourceMappingURL=style.css.map */\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " Blurry Image Report\n", + " \n", + " \n", + "\n", + "\n", + "\n", + "
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Blurry Image Report

Showing example images, sort by ascending order

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Info
blur4.5045
filenamework_dir/crops/framestmpdatavideos6876860979787959554.mp4output_000001.jpg_429_478_38_98.jpg
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blur9.0263
filenamework_dir/crops/framestmpdatavideos6882071585621069058.mp4output_000007.jpg_58_233_100_308.jpg
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blur12.7247
filenamework_dir/crops/framestmpdatavideos6883458545451388161.mp4output_000002.jpg_402_128_43_48.jpg
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blur13.4142
filenamework_dir/crops/framestmpdatavideos6880122437594270978.mp4output_000022.jpg_392_301_27_91.jpg
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blur14.31
filenamework_dir/crops/framestmpdatavideos6876860979787959554.mp4output_000004.jpg_400_498_174_130.jpg
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blur15.0726
filenamework_dir/crops/framestmpdatavideos6882071585621069058.mp4output_000007.jpg_199_220_114_292.jpg
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blur15.7774
filenamework_dir/crops/framestmpdatavideos6881337151901027586.mp4output_000003.jpg_955_154_21_48.jpg
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blur15.9476
filenamework_dir/crops/framestmpdatavideos6882670049648200962.mp4output_000003.jpg_149_797_56_128.jpg
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Info
blur16.0004
filenamework_dir/crops/framestmpdatavideos6882670049648200962.mp4output_000003.jpg_226_818_37_114.jpg
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blur17.1848
filenamework_dir/crops/framestmpdatavideos6876320502848261378.mp4output_000001.jpg_375_737_71_50.jpg
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Info
blur17.2286
filenamework_dir/crops/framestmpdatavideos6878404258367163654.mp4output_000001.jpg_251_682_130_158.jpg
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blur20.8271
filenamework_dir/crops/framestmpdatavideos6882670049648200962.mp4output_000003.jpg_344_838_37_101.jpg
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blur21.7114
filenamework_dir/crops/framestmpdatavideos6880410980434660610.mp4output_000002.jpg_94_934_35_83.jpg
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blur21.9071
filenamework_dir/crops/framestmpdatavideos6880410980434660610.mp4output_000001.jpg_90_933_42_86.jpg
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blur22.4216
filenamework_dir/crops/framestmpdatavideos6880134891753852162.mp4output_000005.jpg_141_445_99_214.jpg
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blur24.3852
filenamework_dir/crops/framestmpdatavideos6878715680728911106.mp4output_000005.jpg_240_557_32_56.jpg
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blur24.9779
filenamework_dir/crops/framestmpdatavideos6879222014880664833.mp4output_000003.jpg_350_228_191_158.jpg
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blur25.1402
filenamework_dir/crops/framestmpdatavideos6875739742340762885.mp4output_000001.jpg_466_694_56_106.jpg
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blur25.6321
filenamework_dir/crops/framestmpdatavideos6884257667573894401.mp4output_000010.jpg_0_143_125_83.jpg
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If you're new, start here!\n", + "+ 🧹 [**Clean Image Folder**](https://nbviewer.org/github/visual-layer/fastdup/blob/main/examples/cleaning-image-dataset.ipynb): Learn how to analyze and clean a folder of images from potential issues and export a list of problematic files for further action. If you have an unorganized folder of images, this is a good place to start.\n", + "+ 🖼 [**Analyze Image Classification Dataset**](https://nbviewer.org/github/visual-layer/fastdup/blob/main/examples/analyzing-image-classification-dataset.ipynb): Learn how to load a labeled image classification dataset and analyze for potential issues. If you have labeled ImageNet-style folder structure, have a go!\n", + "+ 🎁 [**Analyze Object Detection Dataset**](https://nbviewer.org/github/visual-layer/fastdup/blob/main/examples/analyzing-object-detection-dataset.ipynb): Learn how to load bounding box annotations for object detection and analyze for potential issues. If you have a COCO-style labeled object detection dataset, give this example a try. " + ] + }, + { + "cell_type": "markdown", + "id": "934a1fb4", + "metadata": {}, + "source": [ + "\n", + "## VL Profiler\n", + "If you prefer a no-code platform to inspect and visualize your dataset, [**try our free cloud product VL Profiler**](https://app.visual-layer.com) - VL Profiler is our first no-code commercial product that lets you visualize and inspect your dataset in your browser. \n", + "\n", + "[Sign up](https://app.visual-layer.com) now, it's free.\n", + "\n", + "[![image](https://raw.githubusercontent.com/visual-layer/fastdup/main/gallery/vl_profiler_promo.svg)](https://app.visual-layer.com)\n", + "\n", + "As usual, feedback is welcome! \n", + "\n", + "Questions? Drop by our [Slack channel](https://visualdatabase.slack.com/join/shared_invite/zt-19jaydbjn-lNDEDkgvSI1QwbTXSY6dlA#/shared-invite/email) or open an issue on [GitHub](https://github.com/visual-layer/fastdup/issues)." ] } ], From 1b0c7c29807d49d7f5466667819d9a0d3e9de736 Mon Sep 17 00:00:00 2001 From: dnth Date: Wed, 19 Jul 2023 13:30:20 +0800 Subject: [PATCH 3/6] add comments --- examples/video-yolov5-detection.ipynb | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/examples/video-yolov5-detection.ipynb b/examples/video-yolov5-detection.ipynb index 0ab7089e..e66ef739 100644 --- a/examples/video-yolov5-detection.ipynb +++ b/examples/video-yolov5-detection.ipynb @@ -97,7 +97,7 @@ }, { "cell_type": "markdown", - "id": "f21725cb", + "id": "8233b1b7", "metadata": {}, "source": [ "Next, extract the .zip file into a folder named `data`." @@ -124,7 +124,7 @@ "\n", "fastdup works on images. We must first turn the videos into frames of images.\n", "\n", - "We can use a one-liner fastdup utility function to turn all the videos in a folder into frames:" + "We can use a one-liner fastdup utility function to turn all the videos in a folder into frames. This should create a new folder called `frames` that has all the frames from the videos." ] }, { @@ -191,7 +191,7 @@ }, { "cell_type": "markdown", - "id": "737ae835", + "id": "3d1dfd32", "metadata": {}, "source": [ "For demonstration we'll just run on `num_images=2000`, feel free to change its value or omitting it altogether to run it on the entire dataset." From 3744590db5d3466528baa7d8dc3a2b59953beb24 Mon Sep 17 00:00:00 2001 From: dnth Date: Wed, 19 Jul 2023 18:16:47 +0800 Subject: [PATCH 4/6] Run on Russian driving dataset --- examples/video-yolov5-detection.ipynb | 4180 ++++--------------------- 1 file changed, 540 insertions(+), 3640 deletions(-) diff --git a/examples/video-yolov5-detection.ipynb b/examples/video-yolov5-detection.ipynb index e66ef739..57a29ae3 100644 --- a/examples/video-yolov5-detection.ipynb +++ b/examples/video-yolov5-detection.ipynb @@ -78,9 +78,9 @@ "## Download & Extract Dataset\n", "\n", "\n", - "Let's download a Tiktok [trending video dataset](https://www.kaggle.com/datasets/erikvdven/tiktok-trending-december-2020) from Kaggle. The dataset consists of the first 1000 trending videos scraped from TikTok on December 2020.\n", + "Let's download the [Russian car crash dataset](https://www.kaggle.com/datasets/sivoha/car-crash-dataset-russia-2022-2023) from Kaggle. The dataset is a big driving video dataset that contains over 500 high-resolution videos of various driving scenarios\n", "\n", - "You can download the dataset by manually by heading to the dataset [homepage](https://www.kaggle.com/datasets/erikvdven/tiktok-trending-december-2020) or using the [Kaggle API](https://github.com/Kaggle/kaggle-api). \n", + "You can download the dataset by manually by heading to the dataset [homepage](https://www.kaggle.com/datasets/sivoha/car-crash-dataset-russia-2022-2023) or using the [Kaggle API](https://github.com/Kaggle/kaggle-api). \n", "\n", "Let's use the Kaggle API to download the dataset:" ] @@ -88,11 +88,11 @@ { "cell_type": "code", "execution_count": null, - "id": "e9fd45b0", + "id": "9e41ac50", "metadata": {}, "outputs": [], "source": [ - "!kaggle datasets download -d erikvdven/tiktok-trending-december-2020" + "!kaggle datasets download -d sivoha/car-crash-dataset-russia-2022-2023" ] }, { @@ -105,14 +105,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 8, "id": "2e0674a5", "metadata": { "scrolled": true }, "outputs": [], "source": [ - "!unzip -q tiktok-trending-december-2020.zip -d data " + "!unzip -q car-crash-dataset-russia-2022-2023.zip -d data" ] }, { @@ -129,7 +129,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 10, "id": "9258e5af-0802-476b-85ba-2423240a2771", "metadata": { "tags": [] @@ -140,8 +140,8 @@ "output_type": "stream", "text": [ "FastDup Software, (C) copyright 2022 Dr. Amir Alush and Dr. Danny Bickson.\n", - "2023-07-19 13:17:39 [INFO] Going to loop over dir data\n", - "2023-07-19 13:17:39 [INFO] Found total 1000 videos to run on, 1000 train, 0 test, name list 1000, counter 1000 \n" + "2023-07-19 17:56:51 [INFO] Going to loop over dir data/dataset/video\n", + "2023-07-19 17:56:51 [INFO] Found total 548 videos to run on, 548 train, 0 test, name list 548, counter 548 \n" ] }, { @@ -150,13 +150,13 @@ "0" ] }, - "execution_count": 4, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "fastdup.extract_video_frames(input_dir=\"data/\", work_dir=\"frames/\")" + "fastdup.extract_video_frames(input_dir=\"data/dataset/video\", work_dir=\"frames/\")" ] }, { @@ -171,7 +171,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 21, "id": "bd3bf19f-1322-46cc-bfc3-d8db50689367", "metadata": { "tags": [] @@ -199,7 +199,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 22, "id": "29fde366-db7d-4fff-a537-2ff589cddffd", "metadata": { "tags": [] @@ -210,37 +210,39 @@ "output_type": "stream", "text": [ "FastDup Software, (C) copyright 2022 Dr. Amir Alush and Dr. Danny Bickson.\n", - "2023-07-19 13:18:11 [INFO] Going to loop over dir frames\n", - "2023-07-19 13:18:11 [INFO] Found total 2000 images to run on, 2000 train, 0 test, name list 2000, counter 2000 \n", + "2023-07-19 18:05:00 [INFO] Going to loop over dir frames\n", + "2023-07-19 18:05:00 [INFO] Found total 3110 images to run on, 3110 train, 0 test, name list 3110, counter 3110 \n", "FastDup Software, (C) copyright 2022 Dr. Amir Alush and Dr. Danny Bickson.utes\n", - "2023-07-19 13:21:54 [INFO] Going to loop over dir /tmp/crops_input.csv\n", - "2023-07-19 13:21:54 [INFO] Found total 2000 images to run on, 2000 train, 0 test, name list 2000, counter 2000 \n", - "2023-07-19 13:21:59 [INFO] Found total 2000 images to run ontimated: 0 Minutes\n", - "Finished histogram 0.400\n", - "Finished bucket sort 0.409\n", - "2023-07-19 13:21:59 [INFO] 36) Finished write_index() NN model\n", - "2023-07-19 13:21:59 [INFO] Stored nn model index file work_dir/nnf.index\n", - "2023-07-19 13:21:59 [INFO] Total time took 5078 ms\n", - "2023-07-19 13:21:59 [INFO] Found a total of 6 fully identical images (d>0.990), which are 0.15 %\n", - "2023-07-19 13:21:59 [INFO] Found a total of 47 nearly identical images(d>0.980), which are 1.18 %\n", - "2023-07-19 13:21:59 [INFO] Found a total of 844 above threshold images (d>0.900), which are 21.10 %\n", - "2023-07-19 13:21:59 [INFO] Found a total of 200 outlier images (d<0.050), which are 5.00 %\n", - "2023-07-19 13:21:59 [INFO] Min distance found 0.523 max distance 0.995\n", - "2023-07-19 13:21:59 [INFO] Running connected components for ccthreshold 0.960000 \n", + "2023-07-19 18:10:48 [INFO] Going to loop over dir /tmp/crops_input.csv\n", + "2023-07-19 18:10:48 [INFO] Found total 4000 images to run on, 4000 train, 0 test, name list 4000, counter 4000 \n", + "2023-07-19 18:10:48 [ERROR] Image work_dir/crops/framestmpdatadatasetvideow10_12.mp4output_000001.jpg_338_336_6_16.jpg is too small, image size is 22 x 8, min_input_image_width=10\n", + "2023-07-19 18:10:50 [ERROR] Image work_dir/crops/framestmpdatadatasetvideow10_6.mp4output_000002.jpg_728_244_6_12.jpg is too small, image size is 16 x 8, min_input_image_width=10\n", + "2023-07-19 18:10:57 [INFO] Found total 4000 images to run ontimated: 0 Minutes\n", + "Finished histogram 0.774\n", + "Finished bucket sort 0.786\n", + "2023-07-19 18:10:57 [INFO] 57) Finished write_index() NN model\n", + "2023-07-19 18:10:57 [INFO] Stored nn model index file work_dir/nnf.index\n", + "2023-07-19 18:10:57 [INFO] Total time took 9118 ms\n", + "2023-07-19 18:10:57 [INFO] Found a total of 6 fully identical images (d>0.990), which are 0.07 %\n", + "2023-07-19 18:10:57 [INFO] Found a total of 53 nearly identical images(d>0.980), which are 0.66 %\n", + "2023-07-19 18:10:57 [INFO] Found a total of 2828 above threshold images (d>0.900), which are 35.35 %\n", + "2023-07-19 18:10:57 [INFO] Found a total of 399 outlier images (d<0.050), which are 4.99 %\n", + "2023-07-19 18:10:57 [INFO] Min distance found 0.572 max distance 0.995\n", + "2023-07-19 18:10:57 [INFO] Running connected components for ccthreshold 0.960000 \n", ".0\n", " ########################################################################################\n", "\n", "Dataset Analysis Summary: \n", "\n", - " Dataset contains 2000 images\n", - " Valid images are 100.00% (2,000) of the data, invalid are 0.00% (0) of the data\n", - " Similarity: 3.45% (69) belong to 10 similarity clusters (components).\n", - " 96.55% (1,931) images do not belong to any similarity cluster.\n", - " Largest cluster has 28 (1.40%) images.\n", + " Dataset contains 3998 images\n", + " Valid images are 100.00% (3,998) of the data, invalid are 0.00% (0) of the data\n", + " Similarity: 4.20% (168) belong to 16 similarity clusters (components).\n", + " 95.80% (3,830) images do not belong to any similarity cluster.\n", + " Largest cluster has 66 (1.65%) images.\n", " For a detailed analysis, use `.connected_components()`\n", "(similarity threshold used is 0.9, connected component threshold used is 0.96).\n", "\n", - " Outliers: 6.90% (138) of images are possible outliers, and fall in the bottom 5.00% of similarity values.\n", + " Outliers: 6.38% (255) of images are possible outliers, and fall in the bottom 5.00% of similarity values.\n", " For a detailed list of outliers, use `.outliers()`.\n" ] }, @@ -250,13 +252,13 @@ "0" ] }, - "execution_count": 6, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "fd.run(bounding_box='yolov5s', num_images=2000)" + "fd.run(bounding_box='yolov5s')" ] }, { @@ -292,7 +294,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 23, "id": "3edfd955-da16-455d-9089-87ee06161d9c", "metadata": { "scrolled": false, @@ -303,7 +305,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████████████████████████████████████████████████████████████████████| 20/20 [00:00<00:00, 80.17it/s]\n" + "100%|███████████████████████████████████████████| 20/20 [00:00<00:00, 201.77it/s]\n" ] }, { @@ -312,7 +314,7 @@ "text": [ "Finished OK. Components are stored as image files work_dir/galleries/components_[index].jpg\n", "Stored components visual view in work_dir/galleries/components.html\n", - "Execution time in seconds 0.5\n" + "Execution time in seconds 0.4\n" ] }, { @@ -829,7 +831,7 @@ "
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from/crops/tmpdatavideos6881662658794294529.mp4output_000002.jpg_0_107_565_910.jpg/crops/tmpdatadatasetvideow2_37.mp4output_000003.jpg_368_522_50_28.jpg
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Info To
0.900053/crops/tmpdatavideos6881662658794294529.mp4output_000003.jpg_-3_118_573_910.jpg0.900021/crops/tmpdatadatasetvideow10_100.mp4output_000001.jpg_446_404_36_24.jpg
\n", @@ -2008,7 +2017,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2022,7 +2031,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2031,7 +2040,7 @@ "
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from/crops/tmpdatavideos6881662658794294529.mp4output_000003.jpg_-3_118_573_910.jpg/crops/tmpdatadatasetvideow1_59.mp4output_000002.jpg_408_274_50_30.jpg
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Info To
0.900053/crops/tmpdatavideos6881662658794294529.mp4output_000002.jpg_0_107_565_910.jpg0.900029/crops/tmpdatadatasetvideow10_38.mp4output_000001.jpg_754_502_46_26.jpg
\n", @@ -2068,7 +2077,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2082,7 +2091,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2091,7 +2100,7 @@ "
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from/crops/tmpdatavideos6884030480736324869.mp4output_000007.jpg_94_458_85_69.jpg/crops/tmpdatadatasetvideow10_38.mp4output_000001.jpg_754_502_46_26.jpg
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Info To
0.910266/crops/tmpdatavideos6884030480736324869.mp4output_000005.jpg_96_456_86_70.jpg
0.900069/crops/tmpdatavideos6884030480736324869.mp4output_000001.jpg_98_456_85_69.jpg0.900029/crops/tmpdatadatasetvideow1_59.mp4output_000002.jpg_408_274_50_30.jpg
\n", @@ -2132,7 +2137,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2146,7 +2151,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2155,7 +2160,7 @@ "
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from/crops/tmpdatavideos6884031629522717953.mp4output_000004.jpg_213_239_192_518.jpg/crops/tmpdatadatasetvideow2_39.mp4output_000001.jpg_116_374_34_16.jpg
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Info To
0.955997/crops/tmpdatavideos6884031629522717953.mp4output_000005.jpg_222_246_167_510.jpg0.909591/crops/tmpdatadatasetvideow2_24.mp4output_000003.jpg_360_328_36_24.jpg
0.900163/crops/tmpdatavideos6884031629522717953.mp4output_000001.jpg_183_221_171_545.jpg0.900046/crops/tmpdatadatasetvideow2_16.mp4output_000001.jpg_264_370_32_20.jpg
\n", @@ -2196,7 +2201,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2210,7 +2215,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2219,7 +2224,7 @@ "
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from/crops/tmpdatavideos6882598038947286274.mp4output_000002.jpg_42_306_512_549.jpg/crops/tmpdatadatasetvideow2_25.mp4output_000003.jpg_774_432_38_82.jpg
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Info To
0.900303/crops/tmpdatavideos6882598038947286274.mp4output_000004.jpg_5_450_566_376.jpg0.900169/crops/tmpdatadatasetvideow2_25.mp4output_000007.jpg_894_418_48_108.jpg
\n", @@ -2256,7 +2261,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2270,7 +2275,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2279,7 +2284,7 @@ "
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from/crops/tmpdatavideos6882598038947286274.mp4output_000004.jpg_5_450_566_376.jpg/crops/tmpdatadatasetvideow2_25.mp4output_000007.jpg_894_418_48_108.jpg
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Info To
0.900303/crops/tmpdatavideos6882598038947286274.mp4output_000002.jpg_42_306_512_549.jpg0.900169/crops/tmpdatadatasetvideow2_25.mp4output_000003.jpg_774_432_38_82.jpg
\n", @@ -2316,7 +2321,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2330,7 +2335,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2339,7 +2344,7 @@ "
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from/crops/tmpdatavideos6880848041792802053.mp4output_000006.jpg_347_373_98_112.jpg/crops/tmpdatadatasetvideow2_18.mp4output_000011.jpg_376_316_52_22.jpg
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Info To
0.901012/crops/tmpdatavideos6880848041792802053.mp4output_000009.jpg_309_203_88_117.jpg0.900239/crops/tmpdatadatasetvideow2_18.mp4output_000010.jpg_178_322_72_26.jpg
\n", @@ -2376,7 +2381,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2390,7 +2395,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2399,7 +2404,7 @@ "
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from/crops/tmpdatavideos6880848041792802053.mp4output_000009.jpg_309_203_88_117.jpg/crops/tmpdatadatasetvideow2_18.mp4output_000010.jpg_178_322_72_26.jpg
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Info To
0.910023/crops/tmpdatavideos6880848041792802053.mp4output_000001.jpg_205_427_43_56.jpg
0.901012/crops/tmpdatavideos6880848041792802053.mp4output_000006.jpg_347_373_98_112.jpg0.900239/crops/tmpdatadatasetvideow2_18.mp4output_000011.jpg_376_316_52_22.jpg
\n", @@ -2440,7 +2441,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2454,7 +2455,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2463,7 +2464,7 @@ "
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from/crops/tmpdatavideos6880694458552175874.mp4output_000005.jpg_108_65_45_107.jpg/crops/tmpdatadatasetvideow2_13.mp4output_000007.jpg_390_442_136_102.jpg
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Info To
0.901303/crops/tmpdatavideos6880694458552175874.mp4output_000006.jpg_80_60_55_133.jpg0.900271/crops/tmpdatadatasetvideow2_13.mp4output_000004.jpg_314_438_150_112.jpg
\n", @@ -2500,7 +2501,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2514,7 +2515,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2523,7 +2524,7 @@ "
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\n", + "
\n", " \n", " \n", " \n", @@ -2531,26 +2532,22 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatavideos6880694458552175874.mp4output_000006.jpg_80_60_55_133.jpg/crops/tmpdatadatasetvideow2_41.mp4output_000008.jpg_190_266_36_28.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", - "\n", - "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.912736/crops/tmpdatavideos6880694458552175874.mp4output_000005.jpg_79_54_52_135.jpg
0.901303/crops/tmpdatavideos6880694458552175874.mp4output_000005.jpg_108_65_45_107.jpg0.900286/crops/tmpdatadatasetvideow2_41.mp4output_000011.jpg_106_268_46_34.jpg
\n", @@ -2564,7 +2561,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2578,7 +2575,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2587,7 +2584,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2595,22 +2592,26 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatavideos6875394675985992966.mp4output_000001.jpg_354_223_26_81.jpg/crops/tmpdatadatasetvideow2_41.mp4output_000011.jpg_106_268_46_34.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", + "\n", + "\n", + " \n", + " \n", "\n", " \n", "
Info To
0.901346/crops/tmpdatavideos6875394675985992966.mp4output_000001.jpg_376_210_33_95.jpg0.912981/crops/tmpdatadatasetvideow2_41.mp4output_000010.jpg_142_268_44_32.jpg
0.900286/crops/tmpdatadatasetvideow2_41.mp4output_000008.jpg_190_266_36_28.jpg
\n", @@ -2624,7 +2625,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2638,7 +2639,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2647,7 +2648,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2655,22 +2656,26 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatavideos6875394675985992966.mp4output_000001.jpg_376_210_33_95.jpg/crops/tmpdatadatasetvideow2_36.mp4output_000010.jpg_162_352_254_152.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", + "\n", + "\n", + " \n", + " \n", "\n", " \n", "
Info To
0.901346/crops/tmpdatavideos6875394675985992966.mp4output_000001.jpg_354_223_26_81.jpg0.922991/crops/tmpdatadatasetvideow2_36.mp4output_000009.jpg_156_334_262_166.jpg
0.900288/crops/tmpdatadatasetvideow2_36.mp4output_000008.jpg_58_342_304_180.jpg
\n", @@ -2684,7 +2689,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2698,7 +2703,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2707,7 +2712,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2715,26 +2720,26 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatavideos6880848041792802053.mp4output_000008.jpg_323_387_42_51.jpg/crops/tmpdatadatasetvideow2_17.mp4output_000002.jpg_474_304_26_34.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.909584/crops/tmpdatavideos6880848041792802053.mp4output_000010.jpg_258_402_43_50.jpg0.954504/crops/tmpdatadatasetvideow2_17.mp4output_000001.jpg_476_310_22_30.jpg
0.901421/crops/tmpdatavideos6880848041792802053.mp4output_000003.jpg_234_384_48_59.jpg0.900293/crops/tmpdatadatasetvideow1_7.mp4output_000001.jpg_606_372_30_26.jpg
\n", @@ -2748,7 +2753,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2762,7 +2767,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2771,7 +2776,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2779,26 +2784,22 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatavideos6882436135214238981.mp4output_000006.jpg_298_338_67_106.jpg/crops/tmpdatadatasetvideow1_36.mp4output_000001.jpg_1216_384_16_46.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", - "\n", - "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.920284/crops/tmpdatavideos6882770369573358853.mp4output_000002.jpg_283_357_74_112.jpg
0.901421/crops/tmpdatavideos6882436135214238981.mp4output_000007.jpg_285_331_99_147.jpg0.900321/crops/tmpdatadatasetvideow2_16.mp4output_000008.jpg_-2_358_28_16.jpg
\n", @@ -2812,7 +2813,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2826,7 +2827,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2835,7 +2836,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2843,22 +2844,22 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatavideos6877796349459336450.mp4output_000002.jpg_0_450_91_178.jpg/crops/tmpdatadatasetvideow10_131.mp4output_000001.jpg_86_444_14_34.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.901463/crops/tmpdatavideos6877796349459336450.mp4output_000003.jpg_0_448_94_202.jpg0.900332/crops/tmpdatadatasetvideow10_131.mp4output_000001.jpg_240_510_18_46.jpg
\n", @@ -2872,7 +2873,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2886,7 +2887,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2895,7 +2896,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2903,26 +2904,26 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatavideos6878590867968380162.mp4output_000008.jpg_107_138_464_882.jpg/crops/tmpdatadatasetvideow2_100.mp4output_000009.jpg_408_376_214_144.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.94082/crops/tmpdatavideos6878590867968380162.mp4output_000004.jpg_86_226_488_797.jpg0.915737/crops/tmpdatadatasetvideow2_100.mp4output_000012.jpg_392_386_182_148.jpg
0.901571/crops/tmpdatavideos6878590867968380162.mp4output_000010.jpg_22_48_549_971.jpg0.90037/crops/tmpdatadatasetvideow2_100.mp4output_000010.jpg_396_380_180_148.jpg
\n", @@ -2936,7 +2937,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2950,7 +2951,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2959,7 +2960,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2967,22 +2968,22 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatavideos6882436135214238981.mp4output_000003.jpg_32_227_534_795.jpg/crops/tmpdatadatasetvideow1_4.mp4output_000003.jpg_304_358_36_26.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.901692/crops/tmpdatavideos6882436135214238981.mp4output_000005.jpg_110_174_438_853.jpg0.900396/crops/tmpdatadatasetvideow2_39.mp4output_000003.jpg_536_378_32_24.jpg
\n", @@ -2996,7 +2997,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3010,7 +3011,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3019,7 +3020,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -3027,26 +3028,22 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatavideos6882770369573358853.mp4output_000006.jpg_150_208_411_803.jpg/crops/tmpdatadatasetvideow10_47.mp4output_000002.jpg_784_356_52_34.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", - "\n", - "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.906339/crops/tmpdatavideos6882436135214238981.mp4output_000007.jpg_50_123_526_898.jpg
0.901739/crops/tmpdatavideos6882436135214238981.mp4output_000005.jpg_110_174_438_853.jpg0.900452/crops/tmpdatadatasetvideow10_142.mp4output_000001.jpg_532_360_36_28.jpg
\n", @@ -3060,7 +3057,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3074,7 +3071,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3083,7 +3080,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -3091,26 +3088,22 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatavideos6881337151901027586.mp4output_000002.jpg_282_91_56_152.jpg/crops/tmpdatadatasetvideow1_12.mp4output_000001.jpg_686_424_46_34.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", - "\n", - "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.911862/crops/tmpdatavideos6881337151901027586.mp4output_000001.jpg_291_114_50_141.jpg
0.901793/crops/tmpdatavideos6881337151901027586.mp4output_000002.jpg_325_74_51_171.jpg0.900458/crops/tmpdatadatasetvideow1_12.mp4output_000001.jpg_596_420_34_28.jpg
\n", @@ -3124,7 +3117,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3138,7 +3131,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3147,7 +3140,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -3155,26 +3148,22 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatavideos6881337151901027586.mp4output_000002.jpg_325_74_51_171.jpg/crops/tmpdatadatasetvideow1_13.mp4output_000001.jpg_874_400_38_32.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", - "\n", - "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.937144/crops/tmpdatavideos6881337151901027586.mp4output_000001.jpg_333_98_50_165.jpg
0.901793/crops/tmpdatavideos6881337151901027586.mp4output_000002.jpg_282_91_56_152.jpg0.900461/crops/tmpdatadatasetvideow10_139.mp4output_000001.jpg_696_330_38_30.jpg
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Bright Image Report

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Blurry Image Report

Showing example images, sort by ascending order

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blur25.7439
filenamework_dir/crops/framestmpdatavideos6877178763474423041.mp4output_000003.jpg_398_194_178_323.jpg
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\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "0" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], + "source": [ + "fd.vis.stats_gallery(metric='dark')" + ] + }, + { + "cell_type": "markdown", + "id": "8ff9bdf8-89d9-4851-8911-30ca555210b6", + "metadata": {}, + "source": [ + "## Bright Detections" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2d27902d-cd84-4f23-b86b-4eb9cfd7f863", + "metadata": { + "scrolled": false, + "tags": [] + }, + "outputs": [], + "source": [ + "fd.vis.stats_gallery(metric='bright')" + ] + }, + { + "cell_type": "markdown", + "id": "d35bd1bd-a008-417e-9015-e7149e91fb7f", + "metadata": {}, + "source": [ + "## Blurry Detections" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3d9dd6ff-165a-48e3-a498-6e719f253b9a", + "metadata": { + "scrolled": false, + "tags": [] + }, + "outputs": [], "source": [ "fd.vis.stats_gallery(metric='blur')" ] From 1cbac2530737248a92f61625c3664505df5e63dc Mon Sep 17 00:00:00 2001 From: dnth Date: Mon, 24 Jul 2023 15:48:38 +0800 Subject: [PATCH 5/6] rerun on fights video dataset --- examples/video-yolov5-detection.ipynb | 2636 ++++++++++++++++++++----- 1 file changed, 2108 insertions(+), 528 deletions(-) diff --git a/examples/video-yolov5-detection.ipynb b/examples/video-yolov5-detection.ipynb index 57a29ae3..da9842ec 100644 --- a/examples/video-yolov5-detection.ipynb +++ b/examples/video-yolov5-detection.ipynb @@ -31,7 +31,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "1fb73f7e-1bd9-4e8e-b113-94a714abca73", "metadata": {}, "outputs": [], @@ -41,7 +41,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "90d6aea7-f03e-4a9c-ba2c-dee490579304", "metadata": { "tags": [] @@ -57,10 +57,10 @@ { "data": { "text/plain": [ - "'1.27'" + "'1.30'" ] }, - "execution_count": 2, + "execution_count": 1, "metadata": {}, "output_type": "execute_result" } @@ -78,9 +78,9 @@ "## Download & Extract Dataset\n", "\n", "\n", - "Let's download the [Russian car crash dataset](https://www.kaggle.com/datasets/sivoha/car-crash-dataset-russia-2022-2023) from Kaggle. The dataset is a big driving video dataset that contains over 500 high-resolution videos of various driving scenarios\n", + "Let's download the [Video Fight Detection Dataset](https://www.kaggle.com/datasets/naveenk903/movies-fight-detection-dataset) from Kaggle. The dataset consists of real life videos of fight and non-fight scenes meant for video classification task.\n", "\n", - "You can download the dataset by manually by heading to the dataset [homepage](https://www.kaggle.com/datasets/sivoha/car-crash-dataset-russia-2022-2023) or using the [Kaggle API](https://github.com/Kaggle/kaggle-api). \n", + "You can download the dataset by manually by heading to the dataset [homepage](https://www.kaggle.com/datasets/naveenk903/movies-fight-detection-dataset) or using the [Kaggle API](https://github.com/Kaggle/kaggle-api). \n", "\n", "Let's use the Kaggle API to download the dataset:" ] @@ -88,11 +88,11 @@ { "cell_type": "code", "execution_count": null, - "id": "9e41ac50", + "id": "83ac83b8", "metadata": {}, "outputs": [], "source": [ - "!kaggle datasets download -d sivoha/car-crash-dataset-russia-2022-2023" + "!kaggle datasets download -d naveenk903/movies-fight-detection-dataset" ] }, { @@ -105,14 +105,14 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "2e0674a5", "metadata": { "scrolled": true }, "outputs": [], "source": [ - "!unzip -q car-crash-dataset-russia-2022-2023.zip -d data" + "!unzip -q movies-fight-detection-dataset.zip -d data" ] }, { @@ -129,34 +129,14 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "9258e5af-0802-476b-85ba-2423240a2771", "metadata": { "tags": [] }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FastDup Software, (C) copyright 2022 Dr. Amir Alush and Dr. Danny Bickson.\n", - "2023-07-19 17:56:51 [INFO] Going to loop over dir data/dataset/video\n", - "2023-07-19 17:56:51 [INFO] Found total 548 videos to run on, 548 train, 0 test, name list 548, counter 548 \n" - ] - }, - { - "data": { - "text/plain": [ - "0" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "fastdup.extract_video_frames(input_dir=\"data/dataset/video\", work_dir=\"frames/\")" + "fastdup.extract_video_frames(input_dir=\"data/\", work_dir=\"frames/\")" ] }, { @@ -171,7 +151,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 2, "id": "bd3bf19f-1322-46cc-bfc3-d8db50689367", "metadata": { "tags": [] @@ -199,7 +179,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 3, "id": "29fde366-db7d-4fff-a537-2ff589cddffd", "metadata": { "tags": [] @@ -210,78 +190,1501 @@ "output_type": "stream", "text": [ "FastDup Software, (C) copyright 2022 Dr. Amir Alush and Dr. Danny Bickson.\n", - "2023-07-19 18:05:00 [INFO] Going to loop over dir frames\n", - "2023-07-19 18:05:00 [INFO] Found total 3110 images to run on, 3110 train, 0 test, name list 3110, counter 3110 \n", + "2023-07-24 15:37:16 [INFO] Going to loop over dir frames\n", + "2023-07-24 15:37:16 [INFO] Found total 4791 images to run on, 4791 train, 0 test, name list 4791, counter 4791 \n", "FastDup Software, (C) copyright 2022 Dr. Amir Alush and Dr. Danny Bickson.utes\n", - "2023-07-19 18:10:48 [INFO] Going to loop over dir /tmp/crops_input.csv\n", - "2023-07-19 18:10:48 [INFO] Found total 4000 images to run on, 4000 train, 0 test, name list 4000, counter 4000 \n", - "2023-07-19 18:10:48 [ERROR] Image work_dir/crops/framestmpdatadatasetvideow10_12.mp4output_000001.jpg_338_336_6_16.jpg is too small, image size is 22 x 8, min_input_image_width=10\n", - "2023-07-19 18:10:50 [ERROR] Image work_dir/crops/framestmpdatadatasetvideow10_6.mp4output_000002.jpg_728_244_6_12.jpg is too small, image size is 16 x 8, min_input_image_width=10\n", - "2023-07-19 18:10:57 [INFO] Found total 4000 images to run ontimated: 0 Minutes\n", - "Finished histogram 0.774\n", - "Finished bucket sort 0.786\n", - "2023-07-19 18:10:57 [INFO] 57) Finished write_index() NN model\n", - "2023-07-19 18:10:57 [INFO] Stored nn model index file work_dir/nnf.index\n", - "2023-07-19 18:10:57 [INFO] Total time took 9118 ms\n", - "2023-07-19 18:10:57 [INFO] Found a total of 6 fully identical images (d>0.990), which are 0.07 %\n", - "2023-07-19 18:10:57 [INFO] Found a total of 53 nearly identical images(d>0.980), which are 0.66 %\n", - "2023-07-19 18:10:57 [INFO] Found a total of 2828 above threshold images (d>0.900), which are 35.35 %\n", - "2023-07-19 18:10:57 [INFO] Found a total of 399 outlier images (d<0.050), which are 4.99 %\n", - "2023-07-19 18:10:57 [INFO] Min distance found 0.572 max distance 0.995\n", - "2023-07-19 18:10:57 [INFO] Running connected components for ccthreshold 0.960000 \n", + "2023-07-24 15:46:41 [INFO] Going to loop over dir /tmp/crops_input.csv\n", + "2023-07-24 15:46:41 [INFO] Found total 4908 images to run on, 4908 train, 0 test, name list 4908, counter 4908 \n", + "2023-07-24 15:46:54 [INFO] Found total 4908 images to run ontimated: 0 Minutes\n", + "Finished histogram 1.056\n", + "Finished bucket sort 1.071\n", + "2023-07-24 15:46:54 [INFO] 74) Finished write_index() NN model\n", + "2023-07-24 15:46:54 [INFO] Stored nn model index file work_dir/nnf.index\n", + "2023-07-24 15:46:54 [INFO] Total time took 13135 ms\n", + "2023-07-24 15:46:54 [INFO] Found a total of 154 fully identical images (d>0.990), which are 1.57 %\n", + "2023-07-24 15:46:54 [INFO] Found a total of 553 nearly identical images(d>0.980), which are 5.63 %\n", + "2023-07-24 15:46:54 [INFO] Found a total of 7904 above threshold images (d>0.900), which are 80.52 %\n", + "2023-07-24 15:46:54 [INFO] Found a total of 492 outlier images (d<0.050), which are 5.01 %\n", + "2023-07-24 15:46:54 [INFO] Min distance found 0.581 max distance 1.000\n", + "2023-07-24 15:46:54 [INFO] Running connected components for ccthreshold 0.960000 \n", ".0\n", " ########################################################################################\n", "\n", "Dataset Analysis Summary: \n", "\n", - " Dataset contains 3998 images\n", - " Valid images are 100.00% (3,998) of the data, invalid are 0.00% (0) of the data\n", - " Similarity: 4.20% (168) belong to 16 similarity clusters (components).\n", - " 95.80% (3,830) images do not belong to any similarity cluster.\n", - " Largest cluster has 66 (1.65%) images.\n", + " Dataset contains 4908 images\n", + " Valid images are 100.00% (4,908) of the data, invalid are 0.00% (0) of the data\n", + " Similarity: 19.01% (933) belong to 28 similarity clusters (components).\n", + " 80.99% (3,975) images do not belong to any similarity cluster.\n", + " Largest cluster has 128 (2.61%) images.\n", " For a detailed analysis, use `.connected_components()`\n", "(similarity threshold used is 0.9, connected component threshold used is 0.96).\n", "\n", - " Outliers: 6.38% (255) of images are possible outliers, and fall in the bottom 5.00% of similarity values.\n", - " For a detailed list of outliers, use `.outliers()`.\n" + " Outliers: 6.58% (323) of images are possible outliers, and fall in the bottom 5.00% of similarity values.\n", + " For a detailed list of outliers, use `.outliers()`.\n", + "\n" + ] + }, + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fd.run(bounding_box='yolov5s')" + ] + }, + { + "cell_type": "markdown", + "id": "d6098b39-9ac7-4766-a0eb-e5ff255ce05d", + "metadata": {}, + "source": [ + "## Components Gallery\n", + "\n", + "We can visualize the cluster of similar detections using the components gallery view. Specify `draw_bbox=True` to see the detection bounding box on the original image." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c13076de-3cf2-428f-866f-24278b082c02", + "metadata": { + "scrolled": false, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|████████████| 20/20 [00:01<00:00, 17.59it/s]\n", + "/home/dnth/anaconda3/envs/fastdup/lib/python3.10/site-packages/fastdup/galleries.py:933: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " top_components['label'] = top_components['label'].apply(lambda x: x[:MAX_IMAGES_IN_GRID])\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Finished OK. Components are stored as image files work_dir/galleries/components_[index].jpg\n", + "Stored components visual view in work_dir/galleries/components.html\n", + "Execution time in seconds 1.6\n" ] }, + { + "data": { + "text/html": [ + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " Components Report\n", + " \n", + " \n", + "\n", + "\n", + "\n", + "
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Components Report

Showing groups of similar images

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person32
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person28
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person27
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Label
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Info
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Label
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Label
person12
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component2530
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Label
person12
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Label
person12
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Info
component211
num_images12
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Label
person12
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Info
component1012
num_images11
mean_distance0.9654
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Label
person11
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Info
component1645
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Label
person10
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Info
component1668
num_images10
mean_distance0.9603
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Label
person10
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Info
component1563
num_images10
mean_distance0.9722
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Label
person10
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Info
component627
num_images10
mean_distance0.9721
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Label
person10
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Info
component2201
num_images9
mean_distance0.9609
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Label
person9
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\n", "
\n", "
\n", - " \n", + " \n", "
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\n", "
\n", @@ -842,15 +2245,15 @@ " \n", "\n", " component\n", - " 2193\n", + " 692\n", "\n", "\n", " num_images\n", - " 17\n", + " 32\n", "\n", "\n", " mean_distance\n", - " 0.9607\n", + " 0.9617\n", "\n", " \n", " \n", @@ -859,7 +2262,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
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\n", @@ -870,15 +2273,15 @@ " \n", "\n", " component\n", - " 2188\n", + " 637\n", "\n", "\n", " num_images\n", - " 12\n", + " 30\n", "\n", "\n", " mean_distance\n", - " 0.9643\n", + " 0.9601\n", "\n", " \n", " \n", @@ -887,7 +2290,7 @@ "
\n", "
\n", "
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\n", "
\n", "
\n", @@ -898,15 +2301,15 @@ " \n", "\n", " component\n", - " 2945\n", + " 678\n", "\n", "\n", " num_images\n", - " 10\n", + " 27\n", "\n", "\n", " mean_distance\n", - " 0.962\n", + " 0.9708\n", "\n", " \n", " \n", @@ -915,7 +2318,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -926,15 +2329,15 @@ " \n", "\n", " component\n", - " 2949\n", + " 2233\n", "\n", "\n", " num_images\n", - " 10\n", + " 24\n", "\n", "\n", " mean_distance\n", - " 0.9685\n", + " 0.9604\n", "\n", " \n", " \n", @@ -943,7 +2346,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -954,15 +2357,15 @@ " \n", "\n", " component\n", - " 835\n", + " 448\n", "\n", "\n", " num_images\n", - " 8\n", + " 18\n", "\n", "\n", " mean_distance\n", - " 0.963\n", + " 0.9627\n", "\n", " \n", " \n", @@ -971,7 +2374,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -982,11 +2385,11 @@ " \n", "\n", " component\n", - " 3002\n", + " 2132\n", "\n", "\n", " num_images\n", - " 8\n", + " 14\n", "\n", "\n", " mean_distance\n", @@ -999,7 +2402,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1010,15 +2413,15 @@ " \n", "\n", " component\n", - " 637\n", + " 1644\n", "\n", "\n", " num_images\n", - " 8\n", + " 14\n", "\n", "\n", " mean_distance\n", - " 0.9618\n", + " 0.9698\n", "\n", " \n", " \n", @@ -1027,7 +2430,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1038,15 +2441,15 @@ " \n", "\n", " component\n", - " 2968\n", + " 2168\n", "\n", "\n", " num_images\n", - " 8\n", + " 14\n", "\n", "\n", " mean_distance\n", - " 0.9635\n", + " 0.9604\n", "\n", " \n", " \n", @@ -1055,7 +2458,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1066,15 +2469,15 @@ " \n", "\n", " component\n", - " 2916\n", + " 1060\n", "\n", "\n", " num_images\n", - " 7\n", + " 14\n", "\n", "\n", " mean_distance\n", - " 0.9645\n", + " 0.9601\n", "\n", " \n", " \n", @@ -1083,7 +2486,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1094,15 +2497,15 @@ " \n", "\n", " component\n", - " 2912\n", + " 449\n", "\n", "\n", " num_images\n", - " 7\n", + " 13\n", "\n", "\n", " mean_distance\n", - " 0.9647\n", + " 0.9626\n", "\n", " \n", " \n", @@ -1111,7 +2514,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1122,15 +2525,15 @@ " \n", "\n", " component\n", - " 838\n", + " 2448\n", "\n", "\n", " num_images\n", - " 6\n", + " 12\n", "\n", "\n", " mean_distance\n", - " 0.9709\n", + " 0.9636\n", "\n", " \n", " \n", @@ -1139,7 +2542,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1150,15 +2553,15 @@ " \n", "\n", " component\n", - " 3576\n", + " 2530\n", "\n", "\n", " num_images\n", - " 6\n", + " 12\n", "\n", "\n", " mean_distance\n", - " 0.9605\n", + " 0.9618\n", "\n", " \n", " \n", @@ -1167,7 +2570,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1178,15 +2581,15 @@ " \n", "\n", " component\n", - " 3396\n", + " 2772\n", "\n", "\n", " num_images\n", - " 6\n", + " 12\n", "\n", "\n", " mean_distance\n", - " 0.9632\n", + " 0.9621\n", "\n", " \n", " \n", @@ -1195,7 +2598,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1206,15 +2609,15 @@ " \n", "\n", " component\n", - " 2276\n", + " 211\n", "\n", "\n", " num_images\n", - " 6\n", + " 12\n", "\n", "\n", " mean_distance\n", - " 0.9642\n", + " 0.9669\n", "\n", " \n", " \n", @@ -1223,7 +2626,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1234,15 +2637,15 @@ " \n", "\n", " component\n", - " 2299\n", + " 1012\n", "\n", "\n", " num_images\n", - " 6\n", + " 11\n", "\n", "\n", " mean_distance\n", - " 0.9618\n", + " 0.9654\n", "\n", " \n", " \n", @@ -1251,7 +2654,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1262,15 +2665,15 @@ " \n", "\n", " component\n", - " 2914\n", + " 1645\n", "\n", "\n", " num_images\n", - " 5\n", + " 10\n", "\n", "\n", " mean_distance\n", - " 0.9648\n", + " 0.9626\n", "\n", " \n", " \n", @@ -1279,7 +2682,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1290,15 +2693,15 @@ " \n", "\n", " component\n", - " 2194\n", + " 1668\n", "\n", "\n", " num_images\n", - " 5\n", + " 10\n", "\n", "\n", " mean_distance\n", - " 0.9602\n", + " 0.9603\n", "\n", " \n", " \n", @@ -1307,7 +2710,7 @@ "
\n", "
\n", "
\n", - " \n", + " \n", "
\n", "
\n", "
\n", @@ -1318,15 +2721,15 @@ " \n", "\n", " component\n", - " 2016\n", + " 1563\n", "\n", "\n", " num_images\n", - " 5\n", + " 10\n", "\n", "\n", " mean_distance\n", - " 0.9633\n", + " 0.9722\n", "\n", " \n", " \n", @@ -1335,7 +2738,7 @@ "
\n", "
\n", "
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\n", "
\n", @@ -1346,15 +2749,15 @@ " \n", "\n", " component\n", - " 3284\n", + " 627\n", "\n", "\n", " num_images\n", - " 5\n", + " 10\n", "\n", "\n", " mean_distance\n", - " 0.962\n", + " 0.9721\n", "\n", " \n", " \n", @@ -1363,7 +2766,7 @@ "
\n", "
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\n", @@ -1374,15 +2777,15 @@ " \n", "\n", " component\n", - " 1956\n", + " 2201\n", "\n", "\n", " num_images\n", - " 4\n", + " 9\n", "\n", "\n", " mean_distance\n", - " 0.9644\n", + " 0.9609\n", "\n", " \n", " \n", @@ -1410,7 +2813,7 @@ "0" ] }, - "execution_count": 23, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -1431,7 +2834,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 6, "id": "ae3e6a8d-340d-4dfb-a91a-32fde7522325", "metadata": { "scrolled": false, @@ -1449,7 +2852,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|███████████████████████████████████████████| 20/20 [00:00<00:00, 537.21it/s]" + "100%|███████████| 20/20 [00:00<00:00, 184.84it/s]\n" ] }, { @@ -1459,13 +2862,6 @@ "Stored similar images visual view in work_dir/galleries/similarity.html\n" ] }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - }, { "data": { "text/html": [ @@ -1980,7 +3376,7 @@ "
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from/crops/tmpdatadatasetvideow2_37.mp4output_000003.jpg_368_522_50_28.jpg/crops/tmpdataPeliculasfightsnewfi99.avioutput_000001.jpg_425_179_176_244.jpg
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\n", @@ -2017,7 +3413,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2031,7 +3427,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2040,7 +3436,7 @@ "
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from/crops/tmpdatadatasetvideow1_59.mp4output_000002.jpg_408_274_50_30.jpg/crops/tmpdataPeliculasfightsnewfi4.avioutput_000007.jpg_96_25_115_227.jpg
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Info To
0.900029/crops/tmpdatadatasetvideow10_38.mp4output_000001.jpg_754_502_46_26.jpg0.900051/crops/tmpdataPeliculasfightsnewfi4.avioutput_000008.jpg_89_23_109_221.jpg
\n", @@ -2077,7 +3473,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2091,7 +3487,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2100,7 +3496,7 @@ "
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from/crops/tmpdatadatasetvideow10_38.mp4output_000001.jpg_754_502_46_26.jpg/crops/tmpdataPeliculasfightsnewfi79.avioutput_000010.jpg_52_158_65_131.jpg
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Info To
0.900029/crops/tmpdatadatasetvideow1_59.mp4output_000002.jpg_408_274_50_30.jpg0.900077/crops/tmpdataPeliculasfightsnewfi79.avioutput_000011.jpg_115_188_69_149.jpg
\n", @@ -2137,7 +3533,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2151,7 +3547,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2160,7 +3556,7 @@ "
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from/crops/tmpdatadatasetvideow2_39.mp4output_000001.jpg_116_374_34_16.jpg/crops/tmpdataPeliculasfightsnewfi93.avioutput_000026.jpg_289_171_80_205.jpg
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0.909591/crops/tmpdatadatasetvideow2_24.mp4output_000003.jpg_360_328_36_24.jpg
0.900046/crops/tmpdatadatasetvideow2_16.mp4output_000001.jpg_264_370_32_20.jpg0.900082/crops/tmpdataPeliculasfightsnewfi93.avioutput_000024.jpg_288_172_99_200.jpg
\n", @@ -2201,7 +3593,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2215,7 +3607,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2224,7 +3616,7 @@ "
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from/crops/tmpdatadatasetvideow2_25.mp4output_000003.jpg_774_432_38_82.jpg/crops/tmpdataPeliculasfightsnewfi93.avioutput_000024.jpg_288_172_99_200.jpg
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Info To
0.900169/crops/tmpdatadatasetvideow2_25.mp4output_000007.jpg_894_418_48_108.jpg0.900082/crops/tmpdataPeliculasfightsnewfi93.avioutput_000026.jpg_289_171_80_205.jpg
\n", @@ -2261,7 +3653,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2275,7 +3667,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2284,7 +3676,7 @@ "
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from/crops/tmpdatadatasetvideow2_25.mp4output_000007.jpg_894_418_48_108.jpg/crops/tmpdataPeliculasfightsnewfi51.avioutput_000006.jpg_129_92_113_235.jpg
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Info To
0.900169/crops/tmpdatadatasetvideow2_25.mp4output_000003.jpg_774_432_38_82.jpg0.900146/crops/tmpdataPeliculasfightsnewfi51.avioutput_000009.jpg_161_95_83_219.jpg
\n", @@ -2321,7 +3713,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2335,7 +3727,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2344,7 +3736,7 @@ "
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from/crops/tmpdatadatasetvideow2_18.mp4output_000011.jpg_376_316_52_22.jpg/crops/tmpdataPeliculasfightsnewfi66.avioutput_000007.jpg_448_133_129_335.jpg
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Info To
0.900239/crops/tmpdatadatasetvideow2_18.mp4output_000010.jpg_178_322_72_26.jpg0.913802/crops/tmpdataPeliculasfightsnewfi66.avioutput_000006.jpg_468_134_132_330.jpg
0.900177/crops/tmpdataPeliculasfightsnewfi66.avioutput_000005.jpg_473_141_115_327.jpg
\n", @@ -2381,7 +3777,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2395,7 +3791,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2404,7 +3800,7 @@ "
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from/crops/tmpdatadatasetvideow2_18.mp4output_000010.jpg_178_322_72_26.jpg/crops/tmpdataPeliculasfightsnewfi100.avioutput_000021.jpg_186_267_149_124.jpg
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Info To
0.900239/crops/tmpdatadatasetvideow2_18.mp4output_000011.jpg_376_316_52_22.jpg0.900201/crops/tmpdataPeliculasfightsnewfi100.avioutput_000020.jpg_181_266_170_155.jpg
\n", @@ -2441,7 +3837,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2455,7 +3851,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2464,7 +3860,7 @@ "
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from/crops/tmpdatadatasetvideow2_13.mp4output_000007.jpg_390_442_136_102.jpg/crops/tmpdataPeliculasfightsnewfi90.avioutput_000003.jpg_1_69_262_351.jpg
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Info To
0.900271/crops/tmpdatadatasetvideow2_13.mp4output_000004.jpg_314_438_150_112.jpg0.917534/crops/tmpdataPeliculasfightsnewfi90.avioutput_000002.jpg_1_69_262_348.jpg
0.90022/crops/tmpdataPeliculasfightsnewfi90.avioutput_000001.jpg_2_70_282_347.jpg
\n", @@ -2501,7 +3901,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2515,7 +3915,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2524,7 +3924,7 @@ "
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from/crops/tmpdatadatasetvideow2_41.mp4output_000008.jpg_190_266_36_28.jpg/crops/tmpdataPeliculasfightsnewfi90.avioutput_000001.jpg_2_70_282_347.jpg
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Info To
0.900286/crops/tmpdatadatasetvideow2_41.mp4output_000011.jpg_106_268_46_34.jpg0.951013/crops/tmpdataPeliculasfightsnewfi90.avioutput_000002.jpg_1_69_262_348.jpg
0.90022/crops/tmpdataPeliculasfightsnewfi90.avioutput_000003.jpg_1_69_262_351.jpg
\n", @@ -2561,7 +3965,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2575,7 +3979,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2584,7 +3988,7 @@ "
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from/crops/tmpdatadatasetvideow2_41.mp4output_000011.jpg_106_268_46_34.jpg/crops/tmpdataPeliculasfightsnewfi74avi.avioutput_000009.jpg_176_192_74_200.jpg
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Info To
0.912981/crops/tmpdatadatasetvideow2_41.mp4output_000010.jpg_142_268_44_32.jpg
0.900286/crops/tmpdatadatasetvideow2_41.mp4output_000008.jpg_190_266_36_28.jpg0.900355/crops/tmpdataPeliculasfightsnewfi74avi.avioutput_000007.jpg_146_186_91_237.jpg
\n", @@ -2625,7 +4025,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2639,7 +4039,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2648,7 +4048,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2656,26 +4056,22 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatadatasetvideow2_36.mp4output_000010.jpg_162_352_254_152.jpg/crops/tmpdataPeliculasfightsnewfi4.avioutput_000005.jpg_230_110_226_408.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", - "\n", - "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.922991/crops/tmpdatadatasetvideow2_36.mp4output_000009.jpg_156_334_262_166.jpg
0.900288/crops/tmpdatadatasetvideow2_36.mp4output_000008.jpg_58_342_304_180.jpg0.900361/crops/tmpdataPeliculasfightsnewfi4.avioutput_000007.jpg_221_131_261_387.jpg
\n", @@ -2689,7 +4085,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2703,7 +4099,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2712,7 +4108,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2720,26 +4116,26 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatadatasetvideow2_17.mp4output_000002.jpg_474_304_26_34.jpg/crops/tmpdataPeliculasfightsnewfi3.avioutput_000020.jpg_453_290_83_233.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.954504/crops/tmpdatadatasetvideow2_17.mp4output_000001.jpg_476_310_22_30.jpg0.907882/crops/tmpdataPeliculasfightsnewfi19.avioutput_000003.jpg_399_287_83_210.jpg
0.900293/crops/tmpdatadatasetvideow1_7.mp4output_000001.jpg_606_372_30_26.jpg0.900385/crops/tmpdataPeliculasfightsnewfi19.avioutput_000002.jpg_406_289_81_212.jpg
\n", @@ -2753,7 +4149,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2767,7 +4163,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2776,7 +4172,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2784,22 +4180,26 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatadatasetvideow1_36.mp4output_000001.jpg_1216_384_16_46.jpg/crops/tmpdataPeliculasfightsnewfi19.avioutput_000002.jpg_406_289_81_212.jpg
\n", "
\n", "
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\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", + "\n", + "\n", + " \n", + " \n", "\n", " \n", "
Info To
0.900321/crops/tmpdatadatasetvideow2_16.mp4output_000008.jpg_-2_358_28_16.jpg0.966457/crops/tmpdataPeliculasfightsnewfi19.avioutput_000003.jpg_399_287_83_210.jpg
0.900385/crops/tmpdataPeliculasfightsnewfi3.avioutput_000020.jpg_453_290_83_233.jpg
\n", @@ -2813,7 +4213,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2827,7 +4227,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2836,7 +4236,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2844,22 +4244,26 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatadatasetvideow10_131.mp4output_000001.jpg_86_444_14_34.jpg/crops/tmpdataPeliculasfightsnewfi97.avioutput_000050.jpg_168_235_36_48.jpg
\n", "
\n", "
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\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", + "\n", + "\n", + " \n", + " \n", "\n", " \n", "
Info To
0.900332/crops/tmpdatadatasetvideow10_131.mp4output_000001.jpg_240_510_18_46.jpg0.950719/crops/tmpdataPeliculasfightsnewfi97.avioutput_000049.jpg_171_233_33_52.jpg
0.900387/crops/tmpdataPeliculasfightsnewfi97.avioutput_000024.jpg_200_232_24_46.jpg
\n", @@ -2873,7 +4277,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2887,7 +4291,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2896,7 +4300,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2904,26 +4308,26 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatadatasetvideow2_100.mp4output_000009.jpg_408_376_214_144.jpg/crops/tmpdataPeliculasfightsnewfi39.avioutput_000001.jpg_176_69_188_476.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.915737/crops/tmpdatadatasetvideow2_100.mp4output_000012.jpg_392_386_182_148.jpg0.964918/crops/tmpdataPeliculasfightsnewfi39.avioutput_000002.jpg_177_70_186_476.jpg
0.90037/crops/tmpdatadatasetvideow2_100.mp4output_000010.jpg_396_380_180_148.jpg0.900394/crops/tmpdataPeliculasfightsnewfi39.avioutput_000004.jpg_180_70_187_477.jpg
\n", @@ -2937,7 +4341,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2951,7 +4355,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -2960,7 +4364,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2968,14 +4372,14 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatadatasetvideow1_4.mp4output_000003.jpg_304_358_36_26.jpg/crops/tmpdataPeliculasfightsnewfi77.avioutput_000050.jpg_339_143_178_278.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -2983,7 +4387,7 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
0.900396/crops/tmpdatadatasetvideow2_39.mp4output_000003.jpg_536_378_32_24.jpg/crops/tmpdataPeliculasfightsnewfi77.avioutput_000049.jpg_370_158_146_262.jpg
\n", @@ -2997,7 +4401,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3011,7 +4415,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3020,7 +4424,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -3028,22 +4432,22 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatadatasetvideow10_47.mp4output_000002.jpg_784_356_52_34.jpg/crops/tmpdataPeliculasfightsnewfi77.avioutput_000049.jpg_370_158_146_262.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.900452/crops/tmpdatadatasetvideow10_142.mp4output_000001.jpg_532_360_36_28.jpg0.900396/crops/tmpdataPeliculasfightsnewfi77.avioutput_000050.jpg_339_143_178_278.jpg
\n", @@ -3057,7 +4461,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3071,7 +4475,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3080,7 +4484,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -3088,22 +4492,22 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatadatasetvideow1_12.mp4output_000001.jpg_686_424_46_34.jpg/crops/tmpdataPeliculasfightsnewfi86.avioutput_000003.jpg_239_111_68_280.jpg
\n", "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.900458/crops/tmpdatadatasetvideow1_12.mp4output_000001.jpg_596_420_34_28.jpg0.900417/crops/tmpdataPeliculasfightsnewfi86.avioutput_000002.jpg_241_111_71_282.jpg
\n", @@ -3117,7 +4521,7 @@ "\t\t\t\t\t\t\t\t\t\tQuery Image\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3131,7 +4535,7 @@ "\t\t\t\t\t\t\t\t\t\tSimilar\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", - "\t\t\t\t\t\t\t\t\t\t\n", + "\t\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\t\n", "\t\t\t\t\t\t\t\n", @@ -3140,7 +4544,7 @@ "
\n", "
\n", "
\n", - "
\n", + "
\n", " \n", " \n", " \n", @@ -3148,22 +4552,22 @@ " \n", "\n", " \n", - " \n", + " \n", "\n", " \n", "
from/crops/tmpdatadatasetvideow1_13.mp4output_000001.jpg_874_400_38_32.jpg/crops/tmpdataPeliculasfightsnewfi86.avioutput_000002.jpg_241_111_71_282.jpg
\n", "
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\n", + "
\n", " \n", " \n", " \n", " \n", " \n", "\n", - " \n", - " \n", + " \n", + " \n", "\n", " \n", "
Info To
0.900461/crops/tmpdatadatasetvideow10_139.mp4output_000001.jpg_696_330_38_30.jpg0.900417/crops/tmpdataPeliculasfightsnewfi86.avioutput_000003.jpg_239_111_68_280.jpg
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Path/crops/tmpdatadatasetvideow2_26.mp4output_000003.jpg_316_582_116_40.jpg/crops/tmpdataPeliculasfightsnewfi81.avioutput_000007.jpg_145_21_163_450.jpg
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Path/crops/tmpdatadatasetvideow10_37.mp4output_000002.jpg_150_254_422_182.jpg/crops/tmpdataPeliculasfightsnewfi94.avioutput_000021.jpg_305_263_136_84.jpg
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Distance0.6957690.725537
Path/crops/tmpdatadatasetvideow2_40.mp4output_000001.jpg_246_516_82_58.jpg/crops/tmpdataPeliculasfightsnewfi20.avioutput_000024.jpg_7_207_207_78.jpg
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Path/crops/tmpdatadatasetvideow1_14.mp4output_000001.jpg_734_30_90_74.jpg/crops/tmpdataPeliculasfightsnewfi81.avioutput_000019.jpg_169_38_143_43.jpg
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To/crops/tmpdatadatasetvideow2_3.mp4output_000004.jpg_414_370_318_274.jpg/crops/tmpdataPeliculasfightsnewfi1.avioutput_000005.jpg_207_236_116_286.jpg
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To/crops/tmpdatadatasetvideow2_3.mp4output_000004.jpg_414_370_318_274.jpg/crops/tmpdataPeliculasfightsnewfi73.avioutput_000006.jpg_207_203_140_262.jpg
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To/crops/tmpdatadatasetvideow10_42.mp4output_000003.jpg_554_418_20_30.jpg/crops/tmpdataPeliculasfightsnewfi72.avioutput_000004.jpg_439_215_131_245.jpg
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Distance0.9887721.0
From/crops/tmpdatadatasetvideow10_42.mp4output_000001.jpg_554_418_20_30.jpg/crops/tmpdataPeliculasfightsnewfi73.avioutput_000007.jpg_441_215_124_246.jpg
To/crops/tmpdatadatasetvideow10_42.mp4output_000003.jpg_554_418_20_30.jpg/crops/tmpdataPeliculasfightsnewfi72.avioutput_000007.jpg_441_215_124_246.jpg
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To/crops/tmpdatadatasetvideow2_27.mp4output_000001.jpg_1006_60_274_370.jpg/crops/tmpdataPeliculasfightsnewfi72.avioutput_000009.jpg_215_201_123_260.jpg
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Distance1.0
From/crops/tmpdatadatasetvideow2_27.mp4output_000014.jpg_2_24_488_476.jpg/crops/tmpdataPeliculasfightsnewfi73.avioutput_000008.jpg_447_214_116_246.jpg
To/crops/tmpdatadatasetvideow2_27.mp4output_000013.jpg_2_24_482_476.jpg/crops/tmpdataPeliculasfightsnewfi72.avioutput_000008.jpg_447_214_116_246.jpg
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Dark Image Report

Showing example images, sort by ascending order

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mean4.6901
filenamework_dir/crops/framestmpdataPeliculasfightsnewfi96.avioutput_000001.jpg_331_118_89_231.jpg
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mean5.4976
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Bright Image Report

Showing example images, sort by descending order

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Blurry Image Report

Showing example images, sort by ascending order

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blur7.5661
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blur7.8333
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blur8.0188
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blur8.0522
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blur8.1975
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blur8.3127
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blur8.8331
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blur9.4762
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blur9.7096
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blur10.0385
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blur10.0432
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