(input_dir, output_tza, input_names, target_name)
| 74 | |
| 75 | # Preprocesses a group of input and target images at different SPPs |
| 76 | def preprocess_sample_group(input_dir, output_tza, input_names, target_name): |
| 77 | samples = [] |
| 78 | |
| 79 | # Load the target image |
| 80 | target_id = target_name % '' |
| 81 | print(target_id) |
| 82 | target_image, _ = load_image_features(os.path.join(input_dir, target_name), target_features) |
| 83 | |
| 84 | # Compute the autoexposure value |
| 85 | exposure = autoexposure(target_image) if main_feature == 'hdr' else 1. |
| 86 | |
| 87 | # Preprocess the target image |
| 88 | target_image = preprocess_image(target_image, exposure) |
| 89 | |
| 90 | # Save the target image |
| 91 | output_tza.write(target_id, target_image, 'hwc') |
| 92 | |
| 93 | # Process the input images |
| 94 | for input_name in input_names: |
| 95 | # Load the image |
| 96 | input_id = input_name % '' |
| 97 | print(input_id) |
| 98 | input_image, _ = load_image_features(os.path.join(input_dir, input_name), input_features) |
| 99 | |
| 100 | if input_image.shape[0:2] != target_image.shape[0:2]: |
| 101 | error('the input and target images have different sizes') |
| 102 | |
| 103 | # Preprocess the image |
| 104 | input_image = preprocess_image(input_image, exposure, prefilter=True) |
| 105 | |
| 106 | # Save the image |
| 107 | output_tza.write(input_id, input_image, 'hwc') |
| 108 | |
| 109 | # Add sample |
| 110 | samples.append((input_id, target_id)) |
| 111 | |
| 112 | return samples |
| 113 | |
| 114 | # Preprocesses a dataset |
| 115 | def preprocess_dataset(data_name): |
no test coverage detected