source_code_interpretation/plots_py.md #49
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BBuf
reviewed
Dec 6, 2022
| # 设置一些基本的配置 Settings | ||
| RANK = -1 # int(os.getenv('RANK', -1)) | ||
| matplotlib.rc("font", **{"size": 11}) | ||
| # 如果这句话放在import matplotlib.pyplot as plt之前就算加上plt.show()也不会再屏幕上绘图 放在之后其实没什么用 |
| :params file: runs\detect\exp\crops\dog\bus.jpg | ||
| :params gain: 1.02 xyxy缩放因子 | ||
| :params pad: xyxy pad一点点边界框 裁剪出来会更好看 | ||
| :params square: 是否需要将xyxy放缩成正方形 |
| # https://pytorch.org/docs/stable/generated/torch.Tensor.view.html?highlight=torch+view#torch.Tensor.view | ||
| # 其实按照我们通俗的理解就是reshape， | ||
| # 只不过这里是reshape的是张量，也就是将张量重新调整为自己想要的维度（形状大小） | ||
| xyxy = flow.tensor(xyxy).view(-1, 4) # list -> Tensor [1, 4] = [x1 y1 x2 y2] |
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这个tensor的维度是[1, 4]还是[bs, 4]，意思是这个函数的输入只有一个bbox还是可以有很多个bbox呢？
BBuf
reviewed
Dec 6, 2022
| # pd.DataFrame: 创建DataFrame, 类似于一种excel, 表头是['x', 'y', 'width', 'height'] 表格数据: b中数据按行依次存储 | ||
| x = pd.DataFrame(b.transpose(), columns=["x", "y", "width", "height"]) | ||
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| # seaborn correlogram |
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这一节我感觉可以单独做一节教程，就是我之前说过的那个：
2是解析一下one-yolov5训练的时候，train日志里面每张图代表什么以及细节（比如横纵坐标以及计算方法）
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因为这里的代码有点散，很难看得出来下去，如果结合每张图是用哪行画出来的方式就很容易接受了
Co-authored-by: Xiaoyu Zhang <35585791+BBuf@users.noreply.github.com>
Co-authored-by: Xiaoyu Zhang <35585791+BBuf@users.noreply.github.com>
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