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我正在尝试使用tensorflow 检测教程对批处理执行检测,但以下代码给了我setting an array element with a sequence.错误。

# load multiple images 
np_images = []
for img_path in img_paths:
    img = Image.open(image_path)
    image_np = load_image_into_numpy_array(img)      
    image_np_expanded = np.expand_dims(image_np, axis=0)
    np_images.append(image_np)

#Get input and output tensors
image_tensor = det_graph.get_tensor_by_name('image_tensor:0')  
boxes = det_graph.get_tensor_by_name('detection_boxes:0')     
scores = det_graph.get_tensor_by_name('detection_scores:0')
classes = det_graph.get_tensor_by_name('detection_classes:0')
num_detections = det_graph.get_tensor_by_name('num_detections:0')

# detect on batch of images
detection_results = sess.run(
        [boxes, scores, classes, num_detections],
        feed_dict={image_tensor: np_images})  

如何正确输入图像数组?

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1 回答 1

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feed_dict 中的 image_tensor 的维度应该是 [batch_size, x, y, 3],其中 (x,y) 是每个图像的大小。如果您的图像大小都不同,则无法创建这样的 numpy 数组。您可以调整图像大小来解决此问题。

# If the NN was trained on (300,300) size images
IMAGE_SIZE = (300, 300)
for img_path in img_paths:
    img = Image.open(image_path).resize(IMAGE_SIZE)
    image_np = load_image_into_numpy_array(img)      
    np_images.append(image_np)
...
detection_results = sess.run(
    [boxes, scores, classes, num_detections],
    feed_dict={image_tensor: np.array(np_images)}) 
于 2017-12-28T09:32:02.730 回答