使用 Python 的对象检测项目

Question

我正在做一个物体检测项目。我遇到了很多错误，我已经修复了大部分错误，只剩下一个错误。这是我的 google colab 笔记本：https://colab.research.google.com/drive/19mvzDGr0BTV_FgvGwT4DbwccYnPF7SMu.

错误在检测部分。

下面是我检测部分的代码：

with detection_graph.as_default():
    with tf.Session(graph=detection_graph) as sess:
        ret = True
        while (ret):
            ret,image_np = cap.read()

            # Expand dimensions since the model expects images to have shape: [1, None, None, 3]
            image_np_expanded = np.expand_dims(image_np, axis=0)
            image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')

            # Each box represents a part of the image where a particular object was detected.
            boxes = detection_graph.get_tensor_by_name('detection_boxes:0')

            # Each score represent how level of confidence for each of the objects.
            # Score is shown on the result image, together with the class label.
            scores = detection_graph.get_tensor_by_name('detection_scores:0')
            classes = detection_graph.get_tensor_by_name('detection_classes:0')
            num_detections = detection_graph.get_tensor_by_name('num_detections:0')

            # Actual detection.
            (boxes, scores, classes, num_detections) = sess.run(
                [boxes, scores, classes, num_detections],
                feed_dict={image_tensor: image_np_expanded})
                # feed_dict=[image_tensor, image_np_expanded]) 


            # Visualization of the results of a detection.
            vis_util.visualize_boxes_and_labels_on_image_array(
                image_np,
                np.squeeze(boxes),
                np.squeeze(classes).astype(np.int32),
                np.squeeze(scores),
                category_index,
                use_normalized_coordinates=True,
                line_thickness=8)

            cv2.imshow('image',cv2.resize(image_np,(1280,960)))
            if cv2.waitKey(25) & 0xFF == ord('q'):
                cv2.destroyAllWindows()
                cap.release()

                break

这是这段代码的输出或错误：

TypeError                                 Traceback (most recent call last)
<ipython-input-22-7fd26fbacd23> in <module>()
     21             (boxes, scores, classes, num_detections) = sess.run(
     22                 [boxes, scores, classes, num_detections],
---> 23                 feed_dict={image_tensor: image_np_expanded})
     24                 # feed_dict=[image_tensor, image_np_expanded])
     25 

2 frames
/usr/local/lib/python3.6/dist-packages/numpy/core/_asarray.py in asarray(a, dtype, order)
     83 
     84     """
---> 85     return array(a, dtype, copy=False, order=order)
     86 
     87 

TypeError: int() argument must be a string, a bytes-like object or a number, not 'NoneType'

为了更好地理解，请从上面 link.

查看我在 google colab 中的完整项目

Answer 1

错误是因为没有图像被送入。由于您无法直接从 Google Colab 打开网络摄像头，请查看此 question 的答案以了解如何操作。

使用 Python 的对象检测项目

Object detection project using Python

python

machine-learning

object-detection

computer-vision

tensorflow