from keras.layers import Input
from retinanet import Retinanet
from PIL import Image
import numpy as np
import cv2
retinanet = Retinanet()
# 調(diào)用攝像頭
capture=cv2.VideoCapture(0) 
while(True):
    # 讀取某一幀
    ref,frame=capture.read()
    # 格式轉(zhuǎn)變，BGRtoRGB
    frame = cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
    # 轉(zhuǎn)變成Image
    frame = Image.fromarray(np.uint8(frame))
    # 進(jìn)行檢測
    frame = np.array(retinanet.detect_image(frame))
    # RGBtoBGR滿足opencv顯示格式
    frame = cv2.cvtColor(frame,cv2.COLOR_RGB2BGR)
    cv2.imshow("video",frame)
    c= cv2.waitKey(30) & 0xff 
    if c==27:
        capture.release()
        break
retinanet.close_session()

2020/4/26更新：FPS計(jì)算

很多小伙伴說到想要獲取FPS，于是給所有的目標(biāo)檢測網(wǎng)絡(luò)加上了FPS的功能，需要的小伙伴請(qǐng)重新下載。

FPS記錄的原理

FPS簡單來理解就是圖像的刷新頻率，也就是每秒多少幀。

假設(shè)目標(biāo)檢測網(wǎng)絡(luò)處理1幀要0.02s。

此時(shí)FPS就是50。

FPS實(shí)現(xiàn)代碼

該代碼以ssd為例。

#-------------------------------------#
#       調(diào)用攝像頭檢測
#-------------------------------------#
from ssd import SSD
from PIL import Image
import numpy as np
import cv2
import time
ssd = SSD()
# 調(diào)用攝像頭
capture=cv2.VideoCapture(0) # capture=cv2.VideoCapture("1.mp4")
fps = 0.0
while(True):
    t1 = time.time()
    # 讀取某一幀
    ref,frame=capture.read()
    # 格式轉(zhuǎn)變，BGRtoRGB
    frame = cv2.cvtColor(frame,cv2.COLOR_BGR2RGB)
    # 轉(zhuǎn)變成Image
    frame = Image.fromarray(np.uint8(frame))
    # 進(jìn)行檢測
    frame = np.array(ssd.detect_image(frame))
    # RGBtoBGR滿足opencv顯示格式
    frame = cv2.cvtColor(frame,cv2.COLOR_RGB2BGR)
    fps  = ( fps + (1./(time.time()-t1)) ) / 2
    print("fps= %.2f"%(fps))
    frame = cv2.putText(frame, "fps= %.2f"%(fps), (0, 40), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
    cv2.imshow("video",frame)
    c= cv2.waitKey(30) & 0xff 
    if c==27:
        capture.release()
        break

以上就是python利用opencv調(diào)用攝像頭實(shí)現(xiàn)目標(biāo)檢測的詳細(xì)內(nèi)容，更多關(guān)于python opencv調(diào)用攝像頭目標(biāo)檢測的資料請(qǐng)關(guān)注腳本之家其它相關(guān)文章！

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