У меня есть два рабочих файла.Main.py и camera.py файл main.py состоит из функций, вызываемых из файла camera.py, а файл camera.py состоит из моего кода для yolo_webcam.Я получаю NameError: имя 'self' не определено.вот два файла ..
main.py
from flask import Flask, render_template, Response
from camera import VideoCamera
app = Flask(__name__)
@app.route('/')
def index():
return render_template('index.html')
def gen(camera):
while True:
frame = camera.get_frame()
yield (b'--frame\r\n'
b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
@app.route('/video_feed')
def video_feed():
return Response(gen(VideoCamera()),
mimetype='multipart/x-mixed-replace; boundary=frame')
if __name__ == '__main__':
app.run(host='0.0.0.0', debug=True)
camera.py
import cv2
import time
import numpy as np
from keras import backend as K
from keras.models import load_model
from yad2k.models.keras_yolo import yolo_head, yolo_eval
from yad2k.yolo_utils import read_classes, read_anchors, preprocess_webcam_image, draw_boxes, generate_colors
class VideoCamera(object):
def __init__(self):
# Using OpenCV to capture from device 0. If you have trouble capturing
# from a webcam, comment the line below out and use a video file
# instead.
self.video = cv2.VideoCapture(0)
class_names = read_classes("model_data/coco_classes.txt")
anchors = read_anchors("model_data/yolo_anchors.txt")
image_shape = (480., 640.)
yolo_model = load_model("model_data/yolo.h5")
print(yolo_model.summary())
yolo_outputs = yolo_head(yolo_model.output, anchors, len(class_names))
scores, boxes, classes = yolo_eval(yolo_outputs, image_shape)
# If you decide to use video.mp4, you must have this file in the folder
# as the main.py.
# self.video = cv2.VideoCapture('video.mp4')
def predict(sess, frame):
# Preprocess your image
image, image_data = preprocess_webcam_image(frame, model_image_size=(608, 608))
# Run the session with the correct tensors and choose the correct placeholders in the feed_dict.
# You'll need to use feed_dict={yolo_model.input: ... , K.learning_phase(): 0})
out_scores, out_boxes, out_classes = sess.run([scores, boxes, classes], feed_dict={yolo_model.input: image_data,
K.learning_phase(): 0})
# Print predictions info
print('Found {} boxes'.format(len(out_boxes)))
# Generate colors for drawing bounding boxes.
colors = generate_colors(class_names)
# Draw bounding boxes on the image file
draw_boxes(image, out_scores, out_boxes, out_classes, class_names, colors)
return np.array(image)
sess = K.get_session()
while True:
# Capture frame-by-frame
grabbed, frame = self.video.read()
if not grabbed:
break
#Run detection
start = time.time()
output_image = predict(sess, frame)
end = time.time()
print("Inference time: {:.2f}s".format(end - start))
def __del__(self):
self.video.release()
cv2.destroyAllWindows()
def get_frame(self):
success, image = self.video.read()
# We are using Motion JPEG, but OpenCV defaults to capture raw images,
# so we must encode it into JPEG in order to correctly display the
# video stream.
ret, jpeg = cv2.imencode('.jpg', image)
# Display the resulting frame
cv2.imshow('', output_image)
return jpeg.tobytes()
Где я ошибаюсь?Пожалуйста, помогите мне, я новичок.