Question

在我从github获得的工作图像分类中，我必须在终端中输入以下命令 “ python class.py-sample.jpg”，我试图使用摄像头进行实时图像分类，但会引发此错误 TypeError：预期的二进制或Unicode字符串，得到了（真，数组（[[[45，43，41]，........）

import tensorflow as tf
import cv2
import os
# Disable tensorflow compilation warnings
os.environ['TF_CPP_MIN_LOG_LEVEL']='2'
import tensorflow as tf
video_capture = cv2.VideoCapture(0)
#image_path = "frame12.JPEG"
while True:
    ret,frame = video_capture.read()
    # Read the image_data
    image_path = frame
    image_data = tf.gfile.FastGFile(image_path, 'rb').read()
    # Loads label file, strips off carriage return
    label_lines = [line.rstrip() for line
               in tf.gfile.GFile("logs/trained_labels.txt")]
    # Unpersists graph from file
    with tf.gfile.FastGFile("logs/trained_graph.pb", 'rb') as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())
        _ = tf.import_graph_def(graph_def, name='')
    with tf.Session() as sess:
        # Feed the image_data as input to the graph and get first prediction
        softmax_tensor = sess.graph.get_tensor_by_name('final_result:0')
        predictions = sess.run(softmax_tensor, \
         {'DecodeJpeg/contents:0': image_data})
        # Sort to show labels of first prediction in order of confidence
        top_k = predictions[0].argsort()[-len(predictions[0]):][::-1]
        for node_id in top_k:
            human_string = label_lines[node_id]
            score = predictions[0][node_id]
            print('%s (score = %.5f)' % (human_string, score))
    cv2.imshow('Video', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
video_capture.release()
cv2.destroyAllWindows()

使用网络摄像头进行图像分类

0 个答案: