From c683d1f94dd8f03b45de4d0a078ab12b7d55c3a7 Mon Sep 17 00:00:00 2001 From: huanghaian Date: Wed, 21 Sep 2022 10:12:00 +0800 Subject: [PATCH] Fix some config and add description --- configs/yolov5/README.md | 8 +++++--- .../yolov5/yolov5_s-v61_syncbn-detect_8xb16-300e_coco.py | 3 ++- configs/yolov5/yolov5_s-v61_syncbn_8xb16-300e_coco.py | 7 +------ docs/en/algorithm_descriptions/model_design.md | 1 + docs/en/user_guides/config.md | 2 +- 5 files changed, 10 insertions(+), 11 deletions(-) diff --git a/configs/yolov5/README.md b/configs/yolov5/README.md index 322edf53..db701284 100644 --- a/configs/yolov5/README.md +++ b/configs/yolov5/README.md @@ -20,9 +20,11 @@ YOLOv5 is a family of object detection architectures and models pretrained on th **Note**: 1. `fast` means that `YOLOv5DetDataPreprocessor` and `yolov5_collate` are used for data preprocessing, which is faster for training, but less flexible for multitasking. Recommended to use fast version config if you only care about object detection. -2. `SyncBN` means use SyncBN, `AMP` indicates training with mixed precision. -3. We use 8x A100 for training, and the single-GPU batch size is 16. This is different from the official code. -4. The performance is unstable and may fluctuate by about 0.4 mAP. +2. `detect` means that the network input is fixed to `640x640` and the post-processing thresholds is modified. +3. `SyncBN` means use SyncBN, `AMP` indicates training with mixed precision. +4. We use 8x A100 for training, and the single-GPU batch size is 16. This is different from the official code. +5. The performance is unstable and may fluctuate by about 0.4 mAP. +6. `balloon` means that this is a demo configuration. ## Citation diff --git a/configs/yolov5/yolov5_s-v61_syncbn-detect_8xb16-300e_coco.py b/configs/yolov5/yolov5_s-v61_syncbn-detect_8xb16-300e_coco.py index 70750c6c..2789c959 100644 --- a/configs/yolov5/yolov5_s-v61_syncbn-detect_8xb16-300e_coco.py +++ b/configs/yolov5/yolov5_s-v61_syncbn-detect_8xb16-300e_coco.py @@ -16,7 +16,8 @@ test_pipeline = [ 'scale_factor', 'pad_param')) ] -val_dataloader = dict(dataset=dict(pipeline=test_pipeline)) +val_dataloader = dict( + dataset=dict(pipeline=test_pipeline, batch_shapes_cfg=None)) test_dataloader = val_dataloader model = dict( diff --git a/configs/yolov5/yolov5_s-v61_syncbn_8xb16-300e_coco.py b/configs/yolov5/yolov5_s-v61_syncbn_8xb16-300e_coco.py index 3af1a81d..18139ed4 100644 --- a/configs/yolov5/yolov5_s-v61_syncbn_8xb16-300e_coco.py +++ b/configs/yolov5/yolov5_s-v61_syncbn_8xb16-300e_coco.py @@ -188,12 +188,7 @@ val_dataloader = dict( data_prefix=dict(img='val2017/'), ann_file='annotations/instances_val2017.json', pipeline=test_pipeline, - batch_shapes_cfg=dict( - type='BatchShapePolicy', - batch_size=val_batch_size_per_gpu, - img_size=img_scale[0], - size_divisor=32, - extra_pad_ratio=0.5))) + batch_shapes_cfg=batch_shapes_cfg)) test_dataloader = val_dataloader diff --git a/docs/en/algorithm_descriptions/model_design.md b/docs/en/algorithm_descriptions/model_design.md index d0540395..45680b8d 100644 --- a/docs/en/algorithm_descriptions/model_design.md +++ b/docs/en/algorithm_descriptions/model_design.md @@ -3,6 +3,7 @@ ## YOLO series model basic class The structural Graph is provided by RangeKing@GitHub. Thank you RangeKingļ¼ +
base class
diff --git a/docs/en/user_guides/config.md b/docs/en/user_guides/config.md index cffe9944..474b412a 100644 --- a/docs/en/user_guides/config.md +++ b/docs/en/user_guides/config.md @@ -509,7 +509,7 @@ model = dict( ### Reuse variables in \_base\_ file -If the users want to reuse the variables in the base file, they can get a copy of the corresponding variable by using `{{_base_.xxx}}`. The latest version of MMEngine also support reusing variables without `{{}}` usage. +If the users want to reuse the variables in the base file, they can get a copy of the corresponding variable by using `{{_base_.xxx}}`. The latest version of MMEngine also support reusing variables without `{{}}` usage. E.g: