diff --git a/docs/GETTING_STARTED.md b/docs/GETTING_STARTED.md index c0b11d96f74782d70b9ea44a9b0111aca547a17c..3607313030809464a0b3cbfd0f9cdee61e67ee9d 100644 --- a/docs/GETTING_STARTED.md +++ b/docs/GETTING_STARTED.md @@ -38,6 +38,8 @@ python tools/train.py -c configs/faster_rcnn_r50_1x.yml -o use_gpu=false - `--output_eval`: If perform evaluation in training, this edits evaluation directory, default is current directory. - `-d` or `--dataset_dir`: Dataset path, same as `dataset_dir` of configs. Such as: `-d dataset/coco` - `-o`: Set configuration options in config file. Such as: `-o max_iters=180000` +- `--use_tb`: Whether to record the data with [tb-paddle](https://github.com/linshuliang/tb-paddle), so as to display in Tensorboard, default is `False` +- `--tb_log_dir`: tb-paddle logging directory for scalar, default is `tb_log_dir/scalar` ##### Examples @@ -150,10 +152,13 @@ python tools/infer.py -c configs/faster_rcnn_r50_1x.yml --infer_dir=demo - `--output_dir`: Directory for storing the output visualization files. - `--draw_threshold`: Threshold to reserve the result for visualization. Default is 0.5. - `--save_inference_model`: Save inference model in output_dir if True. +- `--use_tb`: Whether to record the data with [tb-paddle](https://github.com/linshuliang/tb-paddle), so as to display in Tensorboard, default is `False` +- `--tb_log_dir`: tb-paddle logging directory for image, default is `tb_log_dir/image` #### Examples - Output specified directory && Set up threshold + ```bash # run on GPU with: export PYTHONPATH=$PYTHONPATH:. @@ -162,11 +167,16 @@ python tools/infer.py -c configs/faster_rcnn_r50_1x.yml \ --infer_img=demo/000000570688.jpg \ --output_dir=infer_output/ \ --draw_threshold=0.5 \ - -o weights=output/faster_rcnn_r50_1x/model_final + -o weights=output/faster_rcnn_r50_1x/model_final \ + --use_tb=Ture ``` -The visualization files are saved in `output` by default, to specify a different -path, simply add a `--output_dir=` flag. -`--draw_threshold` is an optional argument. Default is 0.5. Different thresholds will produce different results depending on the calculation of [NMS](https://ieeexplore.ieee.org/document/1699659). If users want to infer according to customized model path, `-o weights` can be set for specified path. + +The visualization files are saved in `output` by default, to specify a different path, simply add a `--output_dir=` flag. +`--draw_threshold` is an optional argument. Default is 0.5. +Different thresholds will produce different results depending on the calculation of [NMS](https://ieeexplore.ieee.org/document/1699659). +If users want to infer according to customized model path, `-o weights` can be set for specified path. +`--use_tb` is an optional argument, if `--use_tb` is `True`, the tb-paddle will record data in directory, +so users can see the results in Tensorboard. - Save inference model diff --git a/docs/GETTING_STARTED_cn.md b/docs/GETTING_STARTED_cn.md index 2150123e94be4f7c8123b255e5a00ab1436184ae..1eedf7b1e94039417ca1dc199e12d305df30834a 100644 --- a/docs/GETTING_STARTED_cn.md +++ b/docs/GETTING_STARTED_cn.md @@ -39,20 +39,26 @@ python tools/train.py -c configs/faster_rcnn_r50_1x.yml -o use_gpu=false - `--output_eval`: 如果边训练边测试, 这个参数可以编辑评测保存json路径, 默认是当前目录。 - `-d` or `--dataset_dir`: 数据集路径, 同配置文件里的`dataset_dir`. 例如: `-d dataset/coco` - `-o`: 设置配置文件里的参数内容。 例如: `-o max_iters=180000` +- `--use_tb`: 是否使用[tb-paddle](https://github.com/linshuliang/tb-paddle)记录数据，进而在TensorBoard中显示，默认是False。 +- `--tb_log_dir`: 指定 tb-paddle 记录数据的存储路径，默认是`tb_log_dir/scalar`。 ##### 例子 - 边训练边测试 + ```bash export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 export PYTHONPATH=$PYTHONPATH:. python -u tools/train.py -c configs/faster_rcnn_r50_1x.yml --eval ``` -可通过设置`--eval`在训练epoch中交替执行评估, 评估在每个snapshot_iter时开始。可在配置文件的`snapshot_iter`处修改。 -如果验证集很大，测试将会比较耗时，影响训练速度，建议减少评估次数，或训练完再进行评估。当边训练边测试时，在每次snapshot_iter会评测出最佳mAP模型保存到 + +可通过设置`--eval`在训练epoch中交替执行评估, 评估在每个snapshot\_iter时开始。可在配置文件的`snapshot_iter`处修改。 +如果验证集很大，测试将会比较耗时，影响训练速度，建议减少评估次数，或训练完再进行评估。 +当边训练边测试时，在每次snapshot\_iter会评测出最佳mAP模型保存到 `best_model`文件夹下，`best_model`的路径和`model_final`的路径相同。 - 设置配置文件参数 && 指定数据集路径 + ```bash export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 export PYTHONPATH=$PYTHONPATH:. @@ -143,11 +149,14 @@ python tools/infer.py -c configs/faster_rcnn_r50_1x.yml --infer_dir=demo - `--output_dir`: 输出推断后可视化文件。 - `--draw_threshold`: 设置推断的阈值。默认是0.5. -- `--save_inference_model`: 设为`True`时，将预测模型保存到output_dir中. +- `--save_inference_model`: 设为`True`时，将预测模型保存到output\_dir中. +- `--use_tb`: 是否使用[tb-paddle](https://github.com/linshuliang/tb-paddle)记录数据，进而在TensorBoard中显示，默认是False。 +- `--tb_log_dir`: 指定 tb-paddle 记录数据的存储路径，默认是`tb_log_dir/image`。 #### 例子 - 设置输出路径 && 设置推断阈值 + ```bash # GPU推断 export CUDA_VISIBLE_DEVICES=0 @@ -156,12 +165,15 @@ python tools/infer.py -c configs/faster_rcnn_r50_1x.yml \ --infer_img=demo/000000570688.jpg \ --output_dir=infer_output/ \ --draw_threshold=0.5 \ - -o weights=output/faster_rcnn_r50_1x/model_final + -o weights=output/faster_rcnn_r50_1x/model_final \ + --use_tb=True ``` 可视化文件默认保存在`output`中，可通过`--output_dir=`指定不同的输出路径。 -`--draw_threshold` 是个可选参数. 根据 [NMS](https://ieeexplore.ieee.org/document/1699659) 的计算，不同阈值会产生不同的结果。如果用户需要对自定义路径的模型进行推断，可以设置`-o weights`指定模型路径。 +`--draw_threshold` 是个可选参数. 根据 [NMS](https://ieeexplore.ieee.org/document/1699659) 的计算， +不同阈值会产生不同的结果。如果用户需要对自定义路径的模型进行推断，可以设置`-o weights`指定模型路径。 +`--use_tb`是个可选参数，当为`True`时，可使用 TensorBoard 来可视化参数的变化趋势和图片。 - 保存推断模型 diff --git a/requirements.txt b/requirements.txt index 44f58520fce86833d8cee218033412067df7b379..798b006ad7baa3b4f24b4a7db15a63d6d2e533f4 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,3 +1,5 @@ tqdm docstring_parser @ http://github.com/willthefrog/docstring_parser/tarball/master typeguard ; python_version >= '3.4' +tb-paddle +tb-nightly diff --git a/tools/infer.py b/tools/infer.py index 47684ed5de5fd916c06890b0acf8abecc9937fe1..00b2749c96e3cd89109ede32ea60d70e4df66736 100644 --- a/tools/infer.py +++ b/tools/infer.py @@ -211,6 +211,13 @@ def main(): callable(model.is_bbox_normalized): is_bbox_normalized = model.is_bbox_normalized() + # use tb-paddle to log image + if FLAGS.use_tb: + from tb_paddle import SummaryWriter + tb_writer = SummaryWriter(FLAGS.tb_log_dir) + tb_image_step = 0 + tb_image_frame = 0 # each frame can display ten pictures at most. + imid2path = reader.imid2path for iter_id, data in enumerate(reader()): outs = exe.run(infer_prog, @@ -236,10 +243,34 @@ def main(): for im_id in im_ids: image_path = imid2path[int(im_id)] image = Image.open(image_path).convert('RGB') + + # use tb-paddle to log original image + if FLAGS.use_tb: + original_image_np = np.array(image) + tb_writer.add_image( + "original/frame_{}".format(tb_image_frame), + original_image_np, + tb_image_step, + dataformats='HWC') + image = visualize_results(image, int(im_id), catid2name, FLAGS.draw_threshold, bbox_results, mask_results) + + # use tb-paddle to log image with bbox + if FLAGS.use_tb: + infer_image_np = np.array(image) + tb_writer.add_image( + "bbox/frame_{}".format(tb_image_frame), + infer_image_np, + tb_image_step, + dataformats='HWC') + tb_image_step += 1 + if tb_image_step % 10 == 0: + tb_image_step = 0 + tb_image_frame += 1 + save_name = get_save_image_name(FLAGS.output_dir, image_path) logger.info("Detection bbox results save in {}".format(save_name)) image.save(save_name, quality=95) @@ -272,5 +303,15 @@ if __name__ == '__main__': action='store_true', default=False, help="Save inference model in output_dir if True.") + parser.add_argument( + "--use_tb", + type=bool, + default=False, + help="whether to record the data to Tensorboard.") + parser.add_argument( + '--tb_log_dir', + type=str, + default="tb_log_dir/image", + help='Tensorboard logging directory for image.') FLAGS = parser.parse_args() main() diff --git a/tools/train.py b/tools/train.py index c6a40842cd158247b1c0ff50965a5f3411ab4335..eb827e0337311dbc87121ee5e11c63bfbecf8b12 100644 --- a/tools/train.py +++ b/tools/train.py @@ -174,6 +174,14 @@ def main(): save_dir = os.path.join(cfg.save_dir, cfg_name) time_stat = deque(maxlen=cfg.log_iter) best_box_ap_list = [0.0, 0] #[map, iter] + + # use tb-paddle to log data + if FLAGS.use_tb: + from tb_paddle import SummaryWriter + tb_writer = SummaryWriter(FLAGS.tb_log_dir) + tb_loss_step = 0 + tb_mAP_step = 0 + for it in range(start_iter, cfg.max_iters): start_time = end_time end_time = time.time() @@ -183,6 +191,14 @@ def main(): eta = str(datetime.timedelta(seconds=int(eta_sec))) outs = exe.run(train_compile_program, fetch_list=train_values) stats = {k: np.array(v).mean() for k, v in zip(train_keys, outs[:-1])} + + # use tb-paddle to log loss + if FLAGS.use_tb: + if it % cfg.log_iter == 0: + for loss_name, loss_value in stats.items(): + tb_writer.add_scalar(loss_name, loss_value, tb_loss_step) + tb_loss_step += 1 + train_stats.update(stats) logs = train_stats.log() if it % cfg.log_iter == 0: @@ -204,6 +220,12 @@ def main(): box_ap_stats = eval_results( results, eval_feed, cfg.metric, cfg.num_classes, resolution, is_bbox_normalized, FLAGS.output_eval, map_type) + + # use tb_paddle to log mAP + if FLAGS.use_tb: + tb_writer.add_scalar("mAP", box_ap_stats[0], tb_mAP_step) + tb_mAP_step += 1 + if box_ap_stats[0] > best_box_ap_list[0]: best_box_ap_list[0] = box_ap_stats[0] best_box_ap_list[1] = it @@ -239,5 +261,15 @@ if __name__ == '__main__': default=None, type=str, help="Dataset path, same as DataFeed.dataset.dataset_dir") + parser.add_argument( + "--use_tb", + type=bool, + default=False, + help="whether to record the data to Tensorboard.") + parser.add_argument( + '--tb_log_dir', + type=str, + default="tb_log_dir/scalar", + help='Tensorboard logging directory for scalar.') FLAGS = parser.parse_args() main()