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Fix gesture collection notebook to handle both training and testing dataset creation #4

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Fix gesture collection notebook to handle both training and testing dataset creation #4

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138 changes: 67 additions & 71 deletions gesture_data_collection_pose.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -4,15 +4,7 @@
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Matplotlib created a temporary config/cache directory at /tmp/matplotlib-bhsk56tr because the default path (/home/mikyas/.cache/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.\n"
]
}
],
"outputs": [],
"source": [
"import json\n",
"import cv2\n",
Expand All @@ -28,7 +20,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 2,
"metadata": {},
"outputs": [
{
Expand All @@ -37,7 +29,7 @@
"<All keys matched successfully>"
]
},
"execution_count": 4,
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
Expand Down Expand Up @@ -78,7 +70,7 @@
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -91,7 +83,7 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -107,32 +99,28 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"/home/mikyas/data_collection/hand_dataset_train\n",
"/home/mikyas/data_collection/hand_dataset_train\n",
"/home/mikyas/data_collection/hand_dataset_train\n",
"/home/mikyas/data_collection/hand_dataset_train\n",
"/home/mikyas/data_collection/hand_dataset_train\n",
"/home/mikyas/data_collection/hand_dataset_train\n"
]
}
],
"outputs": [],
"source": [
"dir_datasets = '/home/mikyas/data_collection/' #give the path to where you want to save you collected data\n",
"dataset_name = \"hand_dataset_train\" #change this to hand_dataset_test when you are collecting data for test\n",
"no_of_classes = 6\n",
"dir_datasets = 'dataset/' #give the path to where you want to save you collected data\n",
"dataset_name = \"hand_dataset_2class\" #change this to hand_dataset_test when you are collecting data for test\n",
"no_of_classes = 2\n",
"create_directories_for_classes(no_of_classes, dir_datasets, dataset_name )"
]
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"train_or_test = \"testing\" # training or testing"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
Expand All @@ -141,7 +129,7 @@
"False"
]
},
"execution_count": 8,
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
Expand All @@ -162,7 +150,7 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
Expand Down Expand Up @@ -200,7 +188,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -224,7 +212,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -243,7 +231,7 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -265,7 +253,7 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -281,7 +269,7 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -295,13 +283,13 @@
},
{
"cell_type": "code",
"execution_count": 15,
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "375b9e6d61384dc1beb1b7cc25a0666b",
"model_id": "7396f41d9c194036a0002914d2b4c55f",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -315,7 +303,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "380b01ad84b340c1a9342ccea6ad1b46",
"model_id": "000c286288c0469e8401c945fbd51b21",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -329,7 +317,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "d954768e10cf46fb963d60c733baf892",
"model_id": "1f08ce283f0a4a19ba25ce3f2ab0593b",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -343,7 +331,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "13412c28b4ca46a7b41ab27decca0214",
"model_id": "1c85b52eabc74d578bffa6d1137faacf",
"version_major": 2,
"version_minor": 0
},
Expand All @@ -364,7 +352,7 @@
},
{
"cell_type": "code",
"execution_count": 16,
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -383,7 +371,7 @@
},
{
"cell_type": "code",
"execution_count": 17,
"execution_count": 16,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -392,7 +380,7 @@
},
{
"cell_type": "code",
"execution_count": 18,
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -401,7 +389,7 @@
},
{
"cell_type": "code",
"execution_count": 19,
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -410,7 +398,7 @@
},
{
"cell_type": "code",
"execution_count": 20,
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -419,34 +407,41 @@
},
{
"cell_type": "code",
"execution_count": 21,
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"def generate_labels(dir_, dataset_name):\n",
" labels = []\n",
" starting_label = 1\n",
" for i in range(len(os.listdir(dir_))):\n",
" for i in range(no_of_classes):\n",
" dir_to_check = os.path.join(dir_,\"%s\" % (i+1))\n",
" for j in range(len(os.listdir(dir_to_check))):\n",
" labels.append(starting_label)\n",
" starting_label+=1\n",
" labels_to_dict = {\"labels\": labels}\n",
" with open((dir_+'.json'), 'w') as outfile:\n",
" if train_or_test == \"training\":\n",
" filename = dir_+'.json'\n",
" elif train_or_test == \"testing\": \n",
" filename = dir_+'_testing.json'\n",
" else:\n",
" print(\"ERROR: check your `train_or_test` variable\")\n",
" \n",
" with open(filename, 'w') as outfile:\n",
" json.dump(labels_to_dict, outfile)\n",
" return labels "
]
},
{
"cell_type": "code",
"execution_count": 22,
"execution_count": 20,
"metadata": {},
"outputs": [],
"source": [
"def rename_images(dir_):\n",
" overall_count = 0\n",
" #dir_ = dir_+dataset_name\n",
" for i in range(len(os.listdir(dir_))):\n",
" for i in range(no_of_classes):\n",
" dir_to_check = os.path.join(dir_,\"%s\" % (i+1))\n",
" dir_to_check+='/'\n",
" for count, filename in enumerate(os.listdir(dir_to_check)):\n",
Expand All @@ -459,45 +454,46 @@
},
{
"cell_type": "code",
"execution_count": 23,
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"generate_labels(dir_, dataset_name)\n",
"rename_images(dir_)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Pick a cell to execute depending on Training or Testing"
]
},
{
"cell_type": "code",
"execution_count": 41,
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'/home/mikyas/chitoku/data_collection/hand_dataset_test/hand_dataset_test.json'"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"import shutil\n",
"dir_training = dir_datasets +'/training/'#change this to /test/ when you are collecting data for test\n",
"dir_training = dir_datasets +'/' + train_or_test + '/'#change this to /test/ when you are collecting data for test\n",
"try:\n",
" os.makedirs(dir_training)\n",
"except FileExistsError:\n",
" print(os.path.join(\"The following directory was not created because it already exsists\", dir_ , ))\n",
"for i in range(len(os.listdir(dir_))):\n",
"for i in range(no_of_classes):\n",
" dir_to_check = os.path.join(dir_,\"%s\" % (i+1))+'/'\n",
" for count, filename in enumerate(os.listdir(dir_to_check)):\n",
" src = dir_to_check+filename\n",
" shutil.move(src,dir_training)\n",
" os.rmdir(dir_to_check)\n",
"shutil.move(dir_training,dir_)\n",
"shutil.move(dir_+'.json',dir_)"
"if train_or_test == \"training\":\n",
" shutil.move(dir_+'.json',dir_)\n",
"elif train_or_test == \"testing\": \n",
" shutil.move(dir_+'_testing.json',dir_)\n",
"else:\n",
" print(\"ERROR: check your `train_or_test` variable\")"
]
},
{
Expand Down