python开启摄像头以及深度学习实现目标检测 python开启摄像头以及深度学习实现目标检测方法

import pygame.camera
import time
import pygame
import cv2
import numpy as np
 
def surface_to_string(surface):
 """convert pygame surface into string"""
 return pygame.image.tostring(surface, 'RGB')
 
def pygame_to_cvimage(surface):
 """conver pygame surface into cvimage"""
 
 #cv_image = np.zeros(surface.get_size, np.uint8, 3)
 image_string = surface_to_string(surface)
 image_np = np.fromstring(image_string, np.uint8).reshape(480, 640, 3)
 frame = cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB)
 return image_np, frame
 
 
pygame.camera.init()
pygame.camera.list_cameras()
cam = pygame.camera.Camera("/dev/video0", [640, 480])
 
cam.start()
time.sleep(0.1)
screen = pygame.display.set_mode([640, 480])
 
while True:
 image = cam.get_image()
 
 cv_image, frame = pygame_to_cvimage(image)
 
 screen.fill([0, 0, 0])
 screen.blit(image, (0, 0))
 pygame.display.update()
 cv2.imshow('frame', frame)
 key = cv2.waitKey(1)
 if key & 0xFF == ord('q'):
  break
 
 
 #pygame.image.save(image, "pygame1.jpg")
 
cam.stop()
 
 
 

from imutils.video import FPS
import argparse
import imutils
 
 
import v4l2
import fcntl
 
import v4l2capture
import select
import image
 
import pygame.camera
import pygame
import cv2
import numpy as np
import time
 
def surface_to_string(surface):
 """convert pygame surface into string"""
 return pygame.image.tostring(surface, 'RGB')
 
def pygame_to_cvimage(surface):
 """conver pygame surface into cvimage"""
 
 #cv_image = np.zeros(surface.get_size, np.uint8, 3)
 image_string = surface_to_string(surface)
 image_np = np.fromstring(image_string, np.uint8).reshape(480, 640, 3)
 frame = cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB)
 return frame
 
 
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--prototxt", required=True, help="path to caffe deploy prototxt file")
ap.add_argument("-m", "--model", required=True, help="path to caffe pretrained model")
ap.add_argument("-c", "--confidence", type=float, default=0.2, help="minimum probability to filter weak detection")
args = vars(ap.parse_args())
 
CLASSES = ["background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow",
   "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor"]
COLORS = np.random.uniform(0, 255, size=(len(CLASSES), 3))
 
print("[INFO] loading model...")
net = cv2.dnn.readNetFromCaffe(args["prototxt"], args["model"])
 
 
print("[INFO] starting video stream ...")
 
###### opencv ########
#vs = VideoStream(src=1).start()
#
#camera = cv2.VideoCapture(0)
#if not camera.isOpened():
# print("camera is not open")
#time.sleep(2.0)
 
 
###### v4l2 ########
 
#vd = open('/dev/video0', 'r')
#cp = v4l2.v4l2_capability()
#fcntl.ioctl(vd, v4l2.VIDIOC_QUERYCAP, cp)
 
#cp.driver
 
 
##### v4l2_capture
#video = v4l2capture.Video_device("/dev/video0")
#size_x, size_y = video.set_format(640, 480, fourcc= 'MJPEG')
#video.create_buffers(30)
 
#video.queue_all_buffers()
 
#video.start()
 
##### pygame ####
pygame.camera.init()
pygame.camera.list_cameras()
cam = pygame.camera.Camera("/dev/video0", [640, 480])
 
cam.start()
time.sleep(1)
 
fps = FPS().start()
 
 
while True:
 #try:
 # frame = vs.read()
 #except:
 # print("camera is not opened")
 
 #frame = imutils.resize(frame, width=400)
 #(h, w) = frame.shape[:2]
 
 
 #grabbed, frame = camera.read()
 #if not grabbed:
 # break
 #select.select((video,), (), ())
 #frame = video.read_and_queue()
 
 #npfs = np.frombuffer(frame, dtype=np.uint8)
 #print(len(npfs))
 #frame = cv2.imdecode(npfs, cv2.IMREAD_COLOR)
 
 image = cam.get_image()
 frame = pygame_to_cvimage(image)
 
 frame = imutils.resize(frame, width=640)
 blob = cv2.dnn.blobFromImage(frame, 0.00783, (640, 480), 127.5)
 
 net.setInput(blob)
 detections = net.forward()
 
 for i in np.arange(0, detections.shape[2]):
 
  confidence = detections[0, 0, i, 2]
 
  if confidence > args["confidence"]:
 
   idx = int(detections[0, 0, i, 1])
   box = detections[0, 0, i, 3:7]*np.array([640, 480, 640, 480])
   (startX, startY, endX, endY) = box.astype("int")
 
   label = "{}:{:.2f}%".format(CLASSES[idx], confidence*100)
   cv2.rectangle(frame, (startX, startY), (endX, endY), COLORS[idx], 2)
   y = startY - 15 if startY - 15 > 15 else startY + 15
 
   cv2.putText(frame, label, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, COLORS[idx], 2)
 
 cv2.imshow("Frame", frame)
 key = cv2.waitKey(1)& 0xFF
 
 if key ==ord("q"):
  break
 
 
fps.stop()
print("[INFO] elapsed time :{:.2f}".format(fps.elapsed()))
print("[INFO] approx. FPS :{:.2f}".format(fps.fps()))
 
 
 
cv2.destroyAllWindows()
 
#vs.stop()