Fix Windows non-UTF source filenames (#4524)
Co-authored-by: Kayzwer <68285002+Kayzwer@users.noreply.github.com>
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commit
1db9afc2e5
16 changed files with 129 additions and 95 deletions
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@ -634,7 +634,7 @@ class CopyPaste:
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result = cv2.flip(im, 1) # augment segments (flip left-right)
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i = cv2.flip(im_new, 1).astype(bool)
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im[i] = result[i] # cv2.imwrite('debug.jpg', im) # debug
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im[i] = result[i]
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labels['img'] = im
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labels['cls'] = cls
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@ -9,8 +9,6 @@ import cv2
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import numpy as np
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from tqdm import tqdm
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from ultralytics.utils.checks import check_requirements
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def coco91_to_coco80_class():
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"""Converts 91-index COCO class IDs to 80-index COCO class IDs.
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@ -18,7 +16,6 @@ def coco91_to_coco80_class():
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Returns:
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(list): A list of 91 class IDs where the index represents the 80-index class ID and the value is the
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corresponding 91-index class ID.
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"""
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return [
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0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, None, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, None, 24, 25, None,
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@ -119,9 +116,7 @@ def convert_coco(labels_dir='../coco/annotations/', use_segments=False, use_keyp
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if len(ann['segmentation']) == 0:
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segments.append([])
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continue
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if isinstance(ann['segmentation'], dict):
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ann['segmentation'] = rle2polygon(ann['segmentation'])
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if len(ann['segmentation']) > 1:
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elif len(ann['segmentation']) > 1:
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s = merge_multi_segment(ann['segmentation'])
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s = (np.concatenate(s, axis=0) / np.array([w, h])).reshape(-1).tolist()
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else:
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@ -131,9 +126,8 @@ def convert_coco(labels_dir='../coco/annotations/', use_segments=False, use_keyp
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if s not in segments:
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segments.append(s)
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if use_keypoints and ann.get('keypoints') is not None:
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k = (np.array(ann['keypoints']).reshape(-1, 3) / np.array([w, h, 1])).reshape(-1).tolist()
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k = box + k
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keypoints.append(k)
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keypoints.append(box + (np.array(ann['keypoints']).reshape(-1, 3) /
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np.array([w, h, 1])).reshape(-1).tolist())
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# Write
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with open((fn / f).with_suffix('.txt'), 'a') as file:
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@ -237,34 +231,6 @@ def convert_dota_to_yolo_obb(dota_root_path: str):
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convert_label(image_name_without_ext, w, h, orig_label_dir, save_dir)
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def rle2polygon(segmentation):
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"""
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Convert Run-Length Encoding (RLE) mask to polygon coordinates.
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Args:
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segmentation (dict, list): RLE mask representation of the object segmentation.
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Returns:
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(list): A list of lists representing the polygon coordinates for each contour.
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Note:
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Requires the 'pycocotools' package to be installed.
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"""
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check_requirements('pycocotools')
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from pycocotools import mask
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m = mask.decode(segmentation)
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m[m > 0] = 255
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contours, _ = cv2.findContours(m, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_TC89_KCOS)
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polygons = []
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for contour in contours:
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epsilon = 0.001 * cv2.arcLength(contour, True)
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contour_approx = cv2.approxPolyDP(contour, epsilon, True)
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polygon = contour_approx.flatten().tolist()
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polygons.append(polygon)
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return polygons
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def min_index(arr1, arr2):
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"""
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Find a pair of indexes with the shortest distance between two arrays of 2D points.
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@ -144,9 +144,7 @@ def verify_image_label(args):
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if keypoint:
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keypoints = lb[:, 5:].reshape(-1, nkpt, ndim)
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if ndim == 2:
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kpt_mask = np.ones(keypoints.shape[:2], dtype=np.float32)
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kpt_mask = np.where(keypoints[..., 0] < 0, 0.0, kpt_mask)
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kpt_mask = np.where(keypoints[..., 1] < 0, 0.0, kpt_mask)
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kpt_mask = np.where((keypoints[..., 0] < 0) | (keypoints[..., 1] < 0), 0.0, 1.0).astype(np.float32)
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keypoints = np.concatenate([keypoints, kpt_mask[..., None]], axis=-1) # (nl, nkpt, 3)
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lb = lb[:, :5]
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return im_file, lb, shape, segments, keypoints, nm, nf, ne, nc, msg
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