要从Google Colab访问笔记本电脑摄像头,并在直播视频中进行对象检测,可以按照以下步骤进行操作:
import cv2
from google.colab import output
from base64 import b64decode
!pip install pyngrok
from pyngrok import ngrok
ngrok_tunnel = ngrok.connect(8888)
url = ngrok_tunnel.public_url
html = """
<script src="https://webrtc.github.io/adapter/adapter-latest.js"></script>
<script>
var video = document.querySelector("#videoElement");
navigator.mediaDevices.getUserMedia({ video: true })
.then(function(stream) {
video.srcObject = stream;
})
.catch(function(err) {
console.log(err);
});
</script>
<video autoplay="true" id="videoElement"></video>
"""
output.eval_js('new Response(`{html}`).text()', {'html': html})
# 加载对象检测模型
net = cv2.dnn.readNetFromDarknet('yolov3.cfg', 'yolov3.weights')
layer_names = net.getLayerNames()
output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]
# 捕获摄像头的视频流
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
if not ret:
break
# 对视频帧进行对象检测
blob = cv2.dnn.blobFromImage(frame, 0.00392, (416, 416), (0, 0, 0), True, crop=False)
net.setInput(blob)
outs = net.forward(output_layers)
# 处理检测结果
class_ids = []
confidences = []
boxes = []
for out in outs:
for detection in out:
scores = detection[5:]
class_id = np.argmax(scores)
confidence = scores[class_id]
if confidence > 0.5:
# 检测到对象
# 获取对象的位置信息
center_x = int(detection[0] * frame.shape[1])
center_y = int(detection[1] * frame.shape[0])
w = int(detection[2] * frame.shape[1])
h = int(detection[3] * frame.shape[0])
x = int(center_x - w / 2)
y = int(center_y - h / 2)
# 保存对象的相关信息
class_ids.append(class_id)
confidences.append(float(confidence))
boxes.append([x, y, w, h])
# 绘制检测结果
indexes = cv2.dnn.NMSBoxes(boxes, confidences, 0.5, 0.4)
font = cv2.FONT_HERSHEY_SIMPLEX
for i in range(len(boxes)):
if i in indexes:
x, y, w, h = boxes[i]
label = str(class_ids[i])
confidence = confidences[i]
color = (0, 255, 0)
cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)
cv2.putText(frame, label, (x, y - 10), font, 0.5, color, 2)
# 显示检测结果
cv2.imshow('Object Detection', frame)
# 按下'q'键退出循环
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# 释放摄像头和窗口
cap.release()
cv2.destroyAllWindows()
通过以上步骤,你可以在Google Colab中访问笔记本电脑的摄像头,并在直播视频中进行对象检测。请注意,这只是一个简单的示例,你可以根据自己的需求进行修改和扩展。
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