帮助文件 - 把 DepthAI 作为发生器使用¶

如果你想把 DepthAI 集成到你的项目中，这个例子可能会对你有用，因为它把 “如何获得结果”, 和 “用它们 做什么 ”分开了。

这个例子使用 yield 关键字将结果发送到 for 循环，而 for 循环调用了这个方法。

如果你想在你的自定义代码中进一步处理接收到的帧，就能用得上这个例子。

代码¶

import cv2
import depthai


class DepthAI:
    def __init__(self):
        self.device = depthai.Device('', False)

        self.p = self.device.create_pipeline(config={
            "streams": ["metaout", "previewout"],
            "ai": {
                "blob_file": "/path/to/model.blob",
                "blob_file_config": "/path/to/config.json"
            }
        })

        self.detections = []

    def run(self):
        while True:
            nnet_packets, data_packets = self.p.get_available_nnet_and_data_packets()

            for nnet_packet in nnet_packets:
                self.detections = list(nnet_packet.getDetectedObjects())

            for packet in data_packets:
                if packet.stream_name == 'previewout':
                    data = packet.getData()
                    data0 = data[0, :, :]
                    data1 = data[1, :, :]
                    data2 = data[2, :, :]
                    frame = cv2.merge([data0, data1, data2])

                    img_h = frame.shape[0]
                    img_w = frame.shape[1]

                    results = []
                    for detection in self.detections:
                        pt1 = int(detection.x_min * img_w), int(detection.y_min * img_h)
                        pt2 = int(detection.x_max * img_w), int(detection.y_max * img_h)
                        results.append((pt1, pt2))
                    yield frame, results

    def __del__(self):
        del self.p
        del self.device


d = DepthAI()

for frame, results in d.run():
    for pt1, pt2 in results:
        cv2.rectangle(frame, pt1, pt2, (0, 0, 255), 2)
    cv2.imshow('previewout', frame)

    if cv2.waitKey(1) == ord('q'):
        break

del d