Add docstrings to YOLOv5 functions (#12760)

* Add docstrings to top level files

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* Update activations.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

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---------

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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Glenn JocherandUltralyticsAssistant authored and GitHub committed 2024-02-25 14:04:01 +01:00
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commit 41603da162
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@@ -123,6 +123,7 @@ class LoadImagesAndLabelsAndMasks(LoadImagesAndLabels): # for training/testing
self.overlap = overlap
def __getitem__(self, index):
"""Returns a transformed item from the dataset at the specified index, handling indexing and image weighting."""
index = self.indices[index] # linear, shuffled, or image_weights
hyp = self.hyp
@@ -230,7 +231,7 @@ class LoadImagesAndLabelsAndMasks(LoadImagesAndLabels): # for training/testing
return (torch.from_numpy(img), labels_out, self.im_files[index], shapes, masks)
def load_mosaic(self, index):
# YOLOv5 4-mosaic loader. Loads 1 image + 3 random images into a 4-image mosaic
"""Loads 1 image + 3 random images into a 4-image YOLOv5 mosaic, adjusting labels and segments accordingly."""
labels4, segments4 = [], []
s = self.img_size
yc, xc = (int(random.uniform(-x, 2 * s + x)) for x in self.mosaic_border) # mosaic center x, y
@@ -291,6 +292,7 @@ class LoadImagesAndLabelsAndMasks(LoadImagesAndLabels): # for training/testing
@staticmethod
def collate_fn(batch):
"""Custom collation function for DataLoader, batches images, labels, paths, shapes, and segmentation masks."""
img, label, path, shapes, masks = zip(*batch) # transposed
batched_masks = torch.cat(masks, 0)
for i, l in enumerate(label):