Add docstrings to YOLOv5 functions (#12760)
* Add docstrings to top level files * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Add docstrings * Auto-format by https://ultralytics.com/actions * Update activations.py Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Auto-format by https://ultralytics.com/actions --------- Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com> Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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@@ -15,7 +15,7 @@ PREFIX = colorstr("AutoAnchor: ")
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def check_anchor_order(m):
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# Check anchor order against stride order for YOLOv5 Detect() module m, and correct if necessary
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"""Checks and corrects anchor order against stride in YOLOv5 Detect() module if necessary."""
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a = m.anchors.prod(-1).mean(-1).view(-1) # mean anchor area per output layer
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da = a[-1] - a[0] # delta a
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ds = m.stride[-1] - m.stride[0] # delta s
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@@ -26,7 +26,7 @@ def check_anchor_order(m):
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@TryExcept(f"{PREFIX}ERROR")
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def check_anchors(dataset, model, thr=4.0, imgsz=640):
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# Check anchor fit to data, recompute if necessary
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"""Evaluates anchor fit to dataset and adjusts if necessary, supporting customizable threshold and image size."""
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m = model.module.model[-1] if hasattr(model, "module") else model.model[-1] # Detect()
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shapes = imgsz * dataset.shapes / dataset.shapes.max(1, keepdims=True)
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scale = np.random.uniform(0.9, 1.1, size=(shapes.shape[0], 1)) # augment scale
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