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@@ -106,8 +106,8 @@ def show_(imgs, pred, epoch, writer):
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plt.Rectangle((x0, y0), x1 - x0, y1 - y0, fill=False, edgecolor=col[idx], linewidth=1))
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for idx, (a, b) in enumerate(line):
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- ax.scatter(a[1], a[0], c='#871F78', s=2)
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- ax.scatter(b[1], b[0], c='#871F78', s=2)
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+ ax.scatter(a[1], a[0], c='#871F78', s=10)
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+ ax.scatter(b[1], b[0], c='#871F78', s=10)
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ax.plot([a[1], b[1]], [a[0], b[0]], c=col[idx], linewidth=1)
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# 将Matplotlib图像转换为Tensor
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@@ -161,8 +161,8 @@ def show_predict(imgs, pred, t_start):
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if box_score > 0.7 and line_score > 0.9:
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ax.add_patch(
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plt.Rectangle((x0, y0), x1 - x0, y1 - y0, fill=False, edgecolor=col[idx], linewidth=1))
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- ax.scatter(a[1], a[0], c='#871F78', s=2)
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- ax.scatter(b[1], b[0], c='#871F78', s=2)
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+ ax.scatter(a[1], a[0], c='#871F78', s=10)
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+ ax.scatter(b[1], b[0], c='#871F78', s=10)
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ax.plot([a[1], b[1]], [a[0], b[0]], c=col[idx], linewidth=1)
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idx = idx + 1
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t_end = time.time()
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