我正在学习Nicollas renotte关于使用TensorFlow和OpenCV进行实时手势检测的教程,并完成了代码。
import cv2
import numpy as np
import time
category_index = label_map_util.create_category_index_from_labelmap(ANNOTATION_PATH+'/label_map.pbtxt')
cap = cv2.VideoCapture(0)
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
while True:
ret, frame = cap.read()
image_np = np.array(frame)
input_tensor = tf.convert_to_tensor(np.expand_dims(image_np, 0), dtype=tf.float32)
detections = detect_fn(input_tensor)
num_detections = int(detections.pop('num_detections'))
detections = {key: value[0, :num_detections].numpy()
for key, value in detections.items()}
detections['num_detections'] = num_detections
# detection_classes should be ints.
detections['detection_classes'] = detections['detection_classes'].astype(np.int64)
label_id_offset = 1
image_np_with_detections = image_np.copy()
viz_utils.visualize_boxes_and_labels_on_image_array(
image_np_with_detections,
detections['detection_boxes'],
detections['detection_classes']+label_id_offset,
detections['detection_scores'],
category_index,
use_normalized_coordinates=True,
max_boxes_to_draw=5,
min_score_thresh=.5,
agnostic_mode=False)
cv2.imshow('object detection', cv2.resize(image_np_with_detections, (800, 600)))
if cv2.waitKey(1) & 0xFF == ord('q'):
cap.release()
break
cap.release()
detections = detect_fn(input_tensor)
因此,这段代码运行良好,可以识别手势,并在手势周围绘制一个框,然后标记它,但我希望在终端本身中打印已识别手势的名称(用于与pyttx3一起使用,以说出检测到的信号)我尝试只打印检测结果['detection_classes']但它只给予了某种数组作为输出,有人能解释一下我如何打印出用分数检测到对象的名称吗?
提前感谢,堆栈溢出的第一篇文章,所以请对我轻点
1条答案
按热度按时间ffvjumwh1#
detections['detection_classes']
返回检测到的每个边界框的类别id。类别索引是将整数idMap到包含类别的字典的字典,例如
{1: {'id': 1, 'name': 'dog'}, 2: {'id': 2, 'name': 'cat'}, ...}
。因此,如果打印
category_index
,则会得到如下结果:假设您要处理的是字母的手势。
有了这些知识,就很容易打印出检测到的手势的标签。