weight-tests.ipynb

{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import tensorflow.compat.v1 as tf\ntf.disable_v2_behavior()","execution_count":1,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"!git clone https://github.com/agchung/Actualmed-COVID-chestxray-dataset","execution_count":12,"outputs":[{"output_type":"stream","text":"Cloning into 'Actualmed-COVID-chestxray-dataset'...\nremote: Enumerating objects: 10, done.\u001b[K\nremote: Counting objects: 100% (10/10), done.\u001b[K\nremote: Compressing objects: 100% (9/9), done.\u001b[K\nremote: Total 422 (delta 1), reused 6 (delta 1), pack-reused 412\u001b[K\nReceiving objects: 100% (422/422), 1.56 GiB | 15.73 MiB/s, done.\nResolving deltas: 100% (16/16), done.\nChecking out files: 100% (240/240), done.\n","name":"stdout"}]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"import numpy as np\nimport os, argparse\nimport cv2\n\nmapping = {'normal': 0, 'pneumonia': 1, 'COVID-19': 2}\ninv_mapping = {0: 'normal', 1: 'pneumonia', 2: 'COVID-19'}\n\nsess = tf.Session()\ntf.get_default_graph()\nsaver = tf.train.import_meta_graph('../input/covidnetweightstest/model.meta')\nsaver.restore(sess, '../input/covidnetweightstest/model-18540')\ngraph = tf.get_default_graph()\n\ndef crop_top(img, percent=0.15):\n    offset = int(img.shape[0] * percent)\n    return img[offset:]\ndef central_crop(img):\n    size = min(img.shape[0], img.shape[1])\n    offset_h = int((img.shape[0] - size) / 2)\n    offset_w = int((img.shape[1] - size) / 2)\n    return img[offset_h:offset_h + size, offset_w:offset_w + size]\ndef process_image_file(filepath, top_percent, size):\n    img = cv2.imread(filepath)\n    img = crop_top(img, percent=top_percent)\n    img = central_crop(img)\n    img = cv2.resize(img, (size, size))\n    return img","execution_count":2,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nfrom tqdm import tqdm\nimpath = './Actualmed-COVID-chestxray-dataset/images/'\nimgs = os.listdir(impath)","execution_count":15,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"preds = []\nfor image in tqdm(imgs):\n    x = process_image_file(filepath = impath + image, top_percent = 0.08,size =  480)\n    image_tensor = graph.get_tensor_by_name('input_1:0')\n    pred_tensor = graph.get_tensor_by_name('norm_dense_1/Softmax:0')\n    x = x.astype('float32') / 255.0\n    pred = sess.run(pred_tensor, feed_dict={image_tensor: np.expand_dims(x, axis=0)})\n    preds.append(pred.argmax())","execution_count":16,"outputs":[{"output_type":"stream","text":"100%|██████████| 238/238 [02:48<00:00,  1.41it/s]\n","name":"stderr"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"print(preds)","execution_count":18,"outputs":[{"output_type":"stream","text":"[2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 0, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 0, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2, 0, 0, 2, 0, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 2, 2, 2, 2]\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"name":"python3","display_name":"Python 3","language":"python"},"language_info":{"name":"python","version":"3.7.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":4}