(args)
| 12 | return 1 / (1 + np.exp(-x)) |
| 13 | |
| 14 | def postprocess_crf(args): |
| 15 | files = os.listdir(args.sal_path) |
| 16 | |
| 17 | if (not os.path.exists(args.output_path)): |
| 18 | os.makedirs(args.output_path) |
| 19 | |
| 20 | for file in tqdm(files): |
| 21 | |
| 22 | img = cv2.imread(args.input_path+'/'+file, 1) |
| 23 | annos = cv2.imread(args.sal_path+'/'+file, 0) |
| 24 | annos = cv2.resize(annos, (img.shape[1], img.shape[0])) |
| 25 | output = args.output_path+'/'+file |
| 26 | |
| 27 | # Setup the CRF model |
| 28 | d = dcrf.DenseCRF2D(img.shape[1], img.shape[0], args.m) |
| 29 | |
| 30 | anno_norm = annos / 255. |
| 31 | n_energy = -np.log((1.0 - anno_norm + args.epsilon)) / (args.tau * sigmoid(1 - anno_norm)) |
| 32 | p_energy = -np.log(anno_norm + args.epsilon) / (args.tau * sigmoid(anno_norm)) |
| 33 | |
| 34 | U = np.zeros((args.m, img.shape[0] * img.shape[1]), dtype='float32') |
| 35 | U[0, :] = n_energy.flatten() |
| 36 | U[1, :] = p_energy.flatten() |
| 37 | |
| 38 | d.setUnaryEnergy(U) |
| 39 | |
| 40 | d.addPairwiseGaussian(sxy=args.gaussian_sxy, compat=3) |
| 41 | d.addPairwiseBilateral(sxy=args.bilateral_sxy, srgb=args.bilateral_srgb, rgbim=img, compat=5) |
| 42 | |
| 43 | # Do the inference |
| 44 | Q = d.inference(1) |
| 45 | map = np.argmax(Q, axis=0).reshape((img.shape[0], img.shape[1])) |
| 46 | |
| 47 | # Save the output as image |
| 48 | segmented_image = map.astype('uint8')*255 |
| 49 | |
| 50 | nb_blobs, im_with_separated_blobs, stats, _ = cv2.connectedComponentsWithStats(segmented_image) |
| 51 | sizes = stats[:, cv2.CC_STAT_AREA] |
| 52 | |
| 53 | # Sort sizes (ignoring the background at index 0) |
| 54 | sorted_sizes = sorted(sizes[1:], reverse=True) |
| 55 | |
| 56 | # Determine the top K sizes |
| 57 | top_k_sizes = sorted_sizes[:args.num_contours] |
| 58 | |
| 59 | im_result = np.zeros_like(im_with_separated_blobs) |
| 60 | |
| 61 | for index_blob in range(1, nb_blobs): |
| 62 | if sizes[index_blob] in top_k_sizes: |
| 63 | im_result[im_with_separated_blobs == index_blob] = 255 |
| 64 | |
| 65 | segmented_image = im_result |
| 66 | |
| 67 | cv2.imwrite(output, segmented_image) |
| 68 | |
| 69 | def postprocess_thresholding(args): |
| 70 | files = os.listdir(args.sal_path) |
no test coverage detected