我正在使用带有OpenCV和Python的YOLOv3进行实时对象检测。效果很好。目前，我尝试捕获检测到的物体图像并显示在烧瓶中。有人知道如何实现此功能吗？希望有人能帮忙。我根据此链接获得了教程 https://medium.com/analytics-vidhya/real-time-object-detection-using-yolov3-with-opencv-and-python-64c985e14786
import cv2
import numpy as np
import os
import time
import detect as dt
from PIL import Image
labelsPath = os.path.sep.join(["yolo-coco", "coco.names"])
weightsPath = os.path.sep.join(["yolo-coco", "yolov3.weights"])
configPath = os.path.sep.join(["yolo-coco", "yolov3.cfg"])
labelsPath = os.path.sep.join(["yolo-coco", "coco.names"])
LABELS = open(labelsPath).read().strip().split("n")
net = cv2.dnn.readNet(configPath, weightsPath)
layer_names = net.getLayerNames()
outputlayers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]
colors= np.random.uniform(0,255,size=(len(LABELS),3))
#loading image
cap0=cv2.VideoCapture(0) #0 for 1st webcam
cap1=cv2.VideoCapture(1)
font = cv2.FONT_HERSHEY_PLAIN
starting_time= time.time()
frame_id = 0
count = 0
use_cuda = 1
# configPath.cuda()
while True:
ret0,frame0= cap0.read() #
ret1,frame1= cap1.read() #
image = cv2.cvtColor(frame0, cv2.COLOR_BGR2RGB)
im_pil = Image.fromarray(image)
im_pil = im_pil.resize((200, 200))
boxes = dt.do_detect(image, im_pil, 0.5, 0.4, use_cuda)
if (ret0):
frame_id+=1
#print(frame_id)
height,width,channels = frame0.shape
#print (frame.shape)
#detecting objects
blob = cv2.dnn.blobFromImage(frame0,0.00392,(320,320),(0,0,0),True,crop=False) #reduce 416 to 320
net.setInput(blob)
outs = net.forward(outputlayers)
#print(outs)
print(outs[1])
#Showing info on screen/ get confidence score of algorithm in detecting an object in blob
class_ids=[]
confidences=[]
boxes=[]
for out in outs:
#print(out)
for detection in out:
scores = detection[5:]
class_id = np.argmax(scores)
confidence = scores[class_id]
print(confidence)
if confidence > 0.3:
#onject detected
center_x= int(detection[0]*width)
center_y= int(detection[1]*height)
w = int(detection[2]*width)
h = int(detection[3]*height)
#cv2.circle(img,(center_x,center_y),10,(0,255,0),2)
#rectangle co-ordinaters
x=int(center_x - w/2)
y=int(center_y - h/2)
#cv2.rectangle(img,(x,y),(x+w,y+h),(0,255,0),2)
boxes.append([x,y,w,h]) #put all rectangle areas
confidences.append(float(confidence)) #how confidence was that object detected and show that percentage
class_ids.append(class_id) #name of the object tha was detected
indexes = cv2.dnn.NMSBoxes(boxes,confidences,0.4,0.6)
result = open('C:/Users/HP/Miniconda3/envs/count_vechicle/coding/images/frame%04d.txt'%(count), 'w')
for i in range(len(boxes)):
result.write(boxes[i])
count = count + 1
success, image = vidcap.read()
result.close()
if i in indexes:
x,y,w,h = boxes[i]
label = str(LABELS[class_ids[i]])
confidence= confidences[i]
color = colors[class_ids[i]]
cv2.rectangle(frame0,(x,y),(x+w,y+h),color,2)
cv2.putText(frame0,label+" "+str(round(confidence,2)),(x,y+30),font,1,(255,255,255),2)
elapsed_time = time.time() - starting_time
fps=frame_id/elapsed_time
cv2.putText(frame0,"FPS:"+str(round(fps,2)),(10,50),font,2,(0,0,0),1)
cv2.imshow("Image0",frame0)
key = cv2.waitKey(1) #wait 1ms the loop will start again and we will process the next frame
if (ret1):
cv2.imshow("Image1",frame1)
key = cv2.waitKey(1) #wait 1ms the loop will start again and we will process the next frame
if key == 27: #esc key stops the process
break;
cap0.release()
cap1.release()
cv2.destroyAllWindows()
使用检测到的对象的边界框坐标，可以从中裁剪出新图像，然后将其保存以显示。
试试这个：
# extract the bounding box coordinates
(x, y) = (boxes[i][0], boxes[i][1])
(w, h) = (boxes[i][2], boxes[i][3])
crop_img = frame[y:y + h, x:x + w] #frame of video you are looping through
cv2.imwrite(<filename>, crop_img)
更新：根据您的代码：
if i in indexes:
x,y,w,h = boxes[i]
crop_img = frame0[y:y + h, x:x + w]
cv2.imwrite(<filename>, crop_img)
使用框坐标，您可以裁剪该部分
希望对您有所帮助。