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| # Copyright (c) OpenMMLab. All rights reserved. | |
| import argparse | |
| import os | |
| from typing import Sequence | |
| import mmcv | |
| from mmdet.apis import inference_detector, init_detector | |
| from mmengine import Config, DictAction | |
| from mmengine.registry import init_default_scope | |
| from mmengine.utils import ProgressBar | |
| from mmyolo.registry import VISUALIZERS | |
| from mmyolo.utils.misc import auto_arrange_images, get_file_list | |
| def parse_args(): | |
| parser = argparse.ArgumentParser(description='Visualize feature map') | |
| parser.add_argument( | |
| 'img', help='Image path, include image file, dir and URL.') | |
| parser.add_argument('config', help='Config file') | |
| parser.add_argument('checkpoint', help='Checkpoint file') | |
| parser.add_argument( | |
| '--out-dir', default='./output', help='Path to output file') | |
| parser.add_argument( | |
| '--target-layers', | |
| default=['backbone'], | |
| nargs='+', | |
| type=str, | |
| help='The target layers to get feature map, if not set, the tool will ' | |
| 'specify the backbone') | |
| parser.add_argument( | |
| '--preview-model', | |
| default=False, | |
| action='store_true', | |
| help='To preview all the model layers') | |
| parser.add_argument( | |
| '--device', default='cuda:0', help='Device used for inference') | |
| parser.add_argument( | |
| '--score-thr', type=float, default=0.3, help='Bbox score threshold') | |
| parser.add_argument( | |
| '--show', action='store_true', help='Show the featmap results') | |
| parser.add_argument( | |
| '--channel-reduction', | |
| default='select_max', | |
| help='Reduce multiple channels to a single channel') | |
| parser.add_argument( | |
| '--topk', | |
| type=int, | |
| default=4, | |
| help='Select topk channel to show by the sum of each channel') | |
| parser.add_argument( | |
| '--arrangement', | |
| nargs='+', | |
| type=int, | |
| default=[2, 2], | |
| help='The arrangement of featmap when channel_reduction is ' | |
| 'not None and topk > 0') | |
| parser.add_argument( | |
| '--cfg-options', | |
| nargs='+', | |
| action=DictAction, | |
| help='override some settings in the used config, the key-value pair ' | |
| 'in xxx=yyy format will be merged into config file. If the value to ' | |
| 'be overwritten is a list, it should be like key="[a,b]" or key=a,b ' | |
| 'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" ' | |
| 'Note that the quotation marks are necessary and that no white space ' | |
| 'is allowed.') | |
| args = parser.parse_args() | |
| return args | |
| class ActivationsWrapper: | |
| def __init__(self, model, target_layers): | |
| self.model = model | |
| self.activations = [] | |
| self.handles = [] | |
| self.image = None | |
| for target_layer in target_layers: | |
| self.handles.append( | |
| target_layer.register_forward_hook(self.save_activation)) | |
| def save_activation(self, module, input, output): | |
| self.activations.append(output) | |
| def __call__(self, img_path): | |
| self.activations = [] | |
| results = inference_detector(self.model, img_path) | |
| return results, self.activations | |
| def release(self): | |
| for handle in self.handles: | |
| handle.remove() | |
| def main(): | |
| args = parse_args() | |
| cfg = Config.fromfile(args.config) | |
| if args.cfg_options is not None: | |
| cfg.merge_from_dict(args.cfg_options) | |
| init_default_scope(cfg.get('default_scope', 'mmyolo')) | |
| channel_reduction = args.channel_reduction | |
| if channel_reduction == 'None': | |
| channel_reduction = None | |
| assert len(args.arrangement) == 2 | |
| model = init_detector(args.config, args.checkpoint, device=args.device) | |
| if not os.path.exists(args.out_dir) and not args.show: | |
| os.mkdir(args.out_dir) | |
| if args.preview_model: | |
| print(model) | |
| print('\n This flag is only show model, if you want to continue, ' | |
| 'please remove `--preview-model` to get the feature map.') | |
| return | |
| target_layers = [] | |
| for target_layer in args.target_layers: | |
| try: | |
| target_layers.append(eval(f'model.{target_layer}')) | |
| except Exception as e: | |
| print(model) | |
| raise RuntimeError('layer does not exist', e) | |
| activations_wrapper = ActivationsWrapper(model, target_layers) | |
| # init visualizer | |
| visualizer = VISUALIZERS.build(model.cfg.visualizer) | |
| visualizer.dataset_meta = model.dataset_meta | |
| # get file list | |
| image_list, source_type = get_file_list(args.img) | |
| progress_bar = ProgressBar(len(image_list)) | |
| for image_path in image_list: | |
| result, featmaps = activations_wrapper(image_path) | |
| if not isinstance(featmaps, Sequence): | |
| featmaps = [featmaps] | |
| flatten_featmaps = [] | |
| for featmap in featmaps: | |
| if isinstance(featmap, Sequence): | |
| flatten_featmaps.extend(featmap) | |
| else: | |
| flatten_featmaps.append(featmap) | |
| img = mmcv.imread(image_path) | |
| img = mmcv.imconvert(img, 'bgr', 'rgb') | |
| if source_type['is_dir']: | |
| filename = os.path.relpath(image_path, args.img).replace('/', '_') | |
| else: | |
| filename = os.path.basename(image_path) | |
| out_file = None if args.show else os.path.join(args.out_dir, filename) | |
| # show the results | |
| shown_imgs = [] | |
| visualizer.add_datasample( | |
| 'result', | |
| img, | |
| data_sample=result, | |
| draw_gt=False, | |
| show=False, | |
| wait_time=0, | |
| out_file=None, | |
| pred_score_thr=args.score_thr) | |
| drawn_img = visualizer.get_image() | |
| for featmap in flatten_featmaps: | |
| shown_img = visualizer.draw_featmap( | |
| featmap[0], | |
| drawn_img, | |
| channel_reduction=channel_reduction, | |
| topk=args.topk, | |
| arrangement=args.arrangement) | |
| shown_imgs.append(shown_img) | |
| shown_imgs = auto_arrange_images(shown_imgs) | |
| progress_bar.update() | |
| if out_file: | |
| mmcv.imwrite(shown_imgs[..., ::-1], out_file) | |
| if args.show: | |
| visualizer.show(shown_imgs) | |
| if not args.show: | |
| print(f'All done!' | |
| f'\nResults have been saved at {os.path.abspath(args.out_dir)}') | |
| # Please refer to the usage tutorial: | |
| # https://github.com/open-mmlab/mmyolo/blob/main/docs/zh_cn/user_guides/visualization.md # noqa | |
| if __name__ == '__main__': | |
| main() | |