Traceback (most recent call last): File "run.py", line 231, in <module> start() File "run.py", line 217, in start add_audio(output_dir, target_path, args['keep_frames'], args['output_file']) File "/home/reason/Downloads/roop-main/core/utils.py", line 54, in add_audio shutil.move(output_dir + f"/output.mp4", save_to) File "/home/reason/anaconda3/envs/deepfake-roop/lib/python3.8/shutil.py", line 811, in move copy_function(src, real_dst) File "/home/reason/anaconda3/envs/deepfake-roop/lib/python3.8/shutil.py", line 435, in copy2 copyfile(src, dst, follow_symlinks=follow_symlinks) File "/home/reason/anaconda3/envs/deepfake-roop/lib/python3.8/shutil.py", line 264, in copyfile with open(src, 'rb') as fsrc, open(dst, 'wb') as fdst: FileNotFoundError: [Errno 2] No such file or directory: '/home/reason/Documents/MJ/output.mp4'

时间: 2023-12-31 10:06:22 浏览: 217
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浅谈Python traceback的优雅处理

这个错误提示说明程序无法在指定路径找到文件 "/home/reason/Documents/MJ/output.mp4"，可能是因为文件不存在或者路径不正确。请检查文件是否存在，并且确认路径是否正确。如果文件不存在，请确保程序生成了输出文件并且输出文件名正确。如果路径不正确，则需要更改路径以指向正确的文件位置。
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with open('your_file.txt', 'r', encoding='gbk') as file: contents = file.read() 请确保将 'your_file.txt' 替换为实际的文件路径和文件名。通过指定正确的编码格式，你应该能够成功读取文件并避免 ...

with tf.Session() as sess: init = tf.global_variables_initializer() sess.run(init) sess.run(iterator.initializer) # 初始化迭代器 print("step 0, test accuracy %g" % compute_accuracy(test_img, test_label)) start = time.time() for i in range(max_epoch): batch_xs, batch_ys = sess.run(next_batch) # 此batch是个2维tuple，batch[0]是(100，784)的样本数据数组，batch[1]是(100，10)的样本标签数组 sess.run(train_step, feed_dict={xs: batch_xs, ys: batch_ys, keep_prob: keep_prob_rate}) if (i+1) % 50 == 0: print("step %d, test accuracy %g" % ((i+1), compute_accuracy(mnist.test_images, mnist.test_labels))) end = time.time() print('******************************************************') print("运行时间:%.2f秒" % (end - start)) 出现Traceback (most recent call last): File "D:\PycharmProjects\CNN_mnist\lab.py", line 104, in <module> print("step 0, test accuracy %g" % compute_accuracy(test_img, test_label)) File "D:\PycharmProjects\CNN_mnist\lab.py", line 46, in compute_accuracy y_pre = sess.run(prediction, feed_dict={xs: v_xs, keep_prob: 1}) File "D:\Anaconda3\envs\tf26gpu\lib\site-packages\tensorflow\python\client\session.py", line 967, in run result = self._run(None, fetches, feed_dict, options_ptr, File "D:\Anaconda3\envs\tf26gpu\lib\site-packages\tensorflow\python\client\session.py", line 1164, in _run raise ValueError( ValueError: Cannot feed value of shape (10000, 28, 28) for Tensor 'x_input:0', which has shape '(?, 784)'

for i in range(max_epoch): batch_xs, batch_ys = sess.run(next_batch) sess.run(train_step, feed_dict={xs: batch_xs, ys: batch_ys, keep_prob: keep_prob_rate}) if (i+1) % 50 == 0: # 在每个训练步骤...

我对superpoint在github上发布的superpoint_v1.pth文件进行了修改，想提取原图像的特征点并绘制，修改的部分代码如下 ： start1 = time.time() pts, desc, heatmap = fe.run(img) # 转换特征点为cv2.KeyPoint对象 cv_keypoints = [cv2.KeyPoint(point[0], point[1], 1) for point in pts[0]] image_color = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) # 绘制特征点 image_with_keypoints = cv2.drawKeypoints(image_color, cv_keypoints, None, flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS) cv2.imshow('Image with Keypoints', image_with_keypoints) cv2.waitKey(0) cv2.destroyAllWindows() 错误信息如下： Traceback (most recent call last): File "D:/SuperPointPretrainedNetwork-master/demo1.py", line 683, in <module> flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS) cv2.error: C:\projects\opencv-python\opencv\modules\features2d\src\draw.cpp:108: error: (-5) Incorrect type of input image. in function cv::drawKeypoints warning: Error opening file (/build/opencv/modules/videoio/src/cap_ffmpeg_impl.hpp:792) warning: ./assets/icl_snippet/ (/build/opencv/modules/videoio/src/cap_ffmpeg_impl.hpp:793) 我改如何修改

根据错误信息，问题出现在 cv2.drawKeypoints 函数中，错误提示是 "Incorrect type of input image"。这意味着 image_color 的类型不正确。 根据您提供的代码，image_color 是使用 cv2.cvtColor 函数从灰度...
py

python.demo.py

Traceback (most recent call last): File "C:\Users\xieqianyun\AppData\Local\Programs\Python\Python36\lib\site-packages\IPython\core\interactiveshell.py", line 3319, in run_code exec(code_obj, self....
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【高级错误分析】：traceback模块在复杂系统中的高效应用秘籍

Python 的异常处理机制是程序健壮性的重要组成部分，而 traceback 模块则是异常处理中的关键工具。这个模块能够帮助开发者详细地了解错误发生时的调用堆栈信息，使得错误定位和调试变得简单高效。本章我们将从 ...
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