Question

我想使用Tensorflow对象检测API（以及预先训练的模型“ ssd_mobilenet_v1_coco_2017_11_17 / frozen_inference_graph.pb”）仅在给定图片中检测人（上面有人，猫，自行车等）。我应该如何修改以下代码？也许我应该修改此行detection_graph.get_tensor_by_name('detection_classes:0')，但是我不知道该怎么做。请帮我我的朋友们！先感谢您。否则某些参考也将很棒。

def detect_objects(image_np, sess, detection_graph):
# 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})

# 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)
return image_np

Answer 1

如果我对它的理解正确，则必须知道人的类别标签，然后才能在可视化检测结果的部分中为该类别进行选择。假设可以对classes和boxes进行切片。

如何使用tensorflow对象检测API仅检测人而不是整个标签对象？

1 个答案: