yolo_v1_pytorch
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PyTorch implementation of YOLO-v1 including training
Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 1.15.4 to 2.7.2. Release notes Sourced from tensorflow's releases. TensorFlow 2.7.2 Release 2.7.2 This releases introduces several vulnerability fixes: Fixes a code injection in saved_model_cli (CVE-2022-29216) Fixes...
Bumps [opencv-python](https://github.com/skvark/opencv-python) from 4.0.0.21 to 4.2.0.32. Release notes Sourced from opencv-python's releases. 4.2.0.32 opencv-python: https://pypi.org/project/opencv-python/ opencv-contrib-python: https://pypi.org/project/opencv-contrib-python/ opencv-python-headless: https://pypi.org/project/opencv-python-headless/ opencv-contrib-python-headless: https://pypi.org/project/opencv-contrib-python-headless/ OpenCV version 4.2.0. Changes: macOS environment updated from xcode8.3...
As stated in the title.
in voc.py def random_scale(self, img, boxes): WHY img = cv2.resize(img, dsize=(int(w * scale), **h**), interpolation=cv2.INTER_LINEAR) I suggest img = cv2.resize(img, dsize=(int(w * scale), **int(h * scale)**), interpolation=cv2.INTER_LINEAR)
def compute_iou(self,bbox1,bbox2): # 获取box1的第一个维度 N = bbox1.size(0) # 获取box2的第一个维度 M = bbox2.size(0) # Compute left-top coordinate of the intersections # lt = torch.max( # [N, 2] -> [N, 1, 2]...
In `voc.py` module (l. 120) you normalize coordinates such as : ```python xy, wh, label = boxes_xy[b], boxes_wh[b], int(labels[b]) ij = (xy / cell_size).ceil() - 1.0 i, j = int(ij[0]),...
Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 1.15.4 to 2.9.3. Release notes Sourced from tensorflow's releases. TensorFlow 2.9.3 Release 2.9.3 This release introduces several vulnerability fixes: Fixes an overflow in tf.keras.losses.poisson (CVE-2022-41887) Fixes a...