3.43. Gen2 设备上的彩色相机和MobilenetSSD模型解码

这个例子展示了如何在 RGB 预览流上运行mobileetv2ssd模型，以及如何在预览上同时显示 RGB 预览和 mobileetv2ssd 的元数据结果。类似于 Gen2 彩色相机和运行MobilenetSSD模型的例子，只不过解码是在 Myriad 上完成的。

3.43.1. 演示

3.43.2. 设置

请运行以下命令来安装所需的依赖项

Warning

说明：此处安装的是第二代depthai库

python3 -m pip install --extra-index-url https://artifacts.luxonis.com/artifactory/luxonis-python-snapshot-local/ depthai==0.0.2.1+c9a19df719cb668e438d6eafd193cdf60a0d9354 numpy==1.19.5 opencv-python==4.5.1.48

有关更多信息，请参阅 Python API 安装指南

这个示例还需要 mobileenetsdd blob ( mobilenet.blob 文件 )才能工作——您可以从这里下载它。

3.43.3. 源代码

from pathlib import Path
import sys
import cv2
import depthai as dai
import numpy as np
import time

'''
Mobilenet SSD设备端解码演示
  "mobilenet-ssd"模型是旨在执行对象检测的单发多框检测（SSD）网络。该模型是使用Caffe框架实现的。
  有关此模型的详细信息，请查看github仓库库 <https://github.com/chuanqi305/MobileNet-SSD>.
'''

# MobilenetSSD标签文本
label_map = ["background", "aeroplane", "bicycle", "bird", "boat", "bottle", "bus", "car", "cat", "chair", "cow",
             "diningtable", "dog", "horse", "motorbike", "person", "pottedplant", "sheep", "sofa", "train", "tvmonitor"]

syncNN = True

# 首先获取模型
mobilenet_path = str((Path(__file__).parent / Path('models/mobilenet.blob')).resolve().absolute())
if len(sys.argv) > 1:
    mobilenet_path = sys.argv[1]

# 开始定义管道
pipeline = dai.Pipeline()

# 创建彩色相机流
cam_rgb = pipeline.createColorCamera()
cam_rgb.setPreviewSize(300, 300)
cam_rgb.setInterleaved(False)
cam_rgb.setFps(40)

# 定义一个将基于源帧进行预测的神经网络
detectionNetwork = pipeline.createMobileNetDetectionNetwork()
detectionNetwork.setConfidenceThreshold(0.5)
detectionNetwork.setBlobPath(mobilenet_path)
detectionNetwork.setNumInferenceThreads(2)
detectionNetwork.input.setBlocking(False)

cam_rgb.preview.link(detectionNetwork.input)

# 创建输出
xout_rgb = pipeline.createXLinkOut()
xout_rgb.setStreamName("rgb")
if(syncNN):
    detectionNetwork.passthrough.link(xout_rgb.input)
else:
    cam_rgb.preview.link(xout_rgb.input)

xout_nn = pipeline.createXLinkOut()
xout_nn.setStreamName("detections")
detectionNetwork.out.link(xout_nn.input)


# 管道已定义，现在设备已连接到管道
with dai.Device(pipeline) as device:
    # 启动管道
    device.startPipeline()

    # 输出队列将用于从上面定义的输出中获取rgb帧和nn数据
    q_rgb = device.getOutputQueue(name="rgb", maxSize=4, blocking=False)
    q_nn = device.getOutputQueue(name="detections", maxSize=4, blocking=False)

    frame = None
    bboxes = []

    start_time = time.time()
    counter = 0
    fps = 0
    while True:
        if(syncNN):
            in_rgb = q_rgb.get()
            in_nn = q_nn.get()
        else:
            in_rgb = q_rgb.tryGet()
            in_nn = q_nn.tryGet()

        if in_rgb is not None:
            # 如果来自RGB相机的数据不为空，则将1维数据转换为HxWxC帧
            shape = (3, in_rgb.getHeight(), in_rgb.getWidth())
            frame = in_rgb.getData().reshape(shape).transpose(1, 2, 0).astype(np.uint8)
            frame = np.ascontiguousarray(frame)

        if in_nn is not None:
            bboxes = in_nn.detections
            counter+=1
            current_time = time.time()
            if (current_time - start_time) > 1 :
                fps = counter / (current_time - start_time)
                counter = 0
                start_time = current_time

        color = (255, 255, 255)

        if frame is not None:
            # 如果图像不为空，请在其上绘制边框并显示图像
            height = frame.shape[0]
            width  = frame.shape[1]
            for bbox in bboxes:
                x1 = int(bbox.xmin * width)
                x2 = int(bbox.xmax * width)
                y1 = int(bbox.ymin * height)
                y2 = int(bbox.ymax * height)
                try:
                    label = label_map[bbox.label]
                except:
                    label = bbox.label
                cv2.putText(frame, str(label), (x1 + 10, y1 + 20), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color)
                cv2.putText(frame, "{:.2f}".format(bbox.confidence*100), (x1 + 10, y1 + 40), cv2.FONT_HERSHEY_TRIPLEX, 0.5, color)
                cv2.rectangle(frame, (x1, y1), (x2, y2), color, cv2.FONT_HERSHEY_SIMPLEX)

            cv2.putText(frame, "NN fps: {:.2f}".format(fps), (2, frame.shape[0] - 4), cv2.FONT_HERSHEY_TRIPLEX, 0.4, color)
            cv2.imshow("rgb", frame)

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