A simple script with simple DepthAI pipeline init and preview

depthai-minimal.py

import consts.resource_paths
import cv2
import depthai

if not depthai.init_device(consts.resource_paths.device_cmd_fpath):
    raise RuntimeError("Error initializing device. Try to reset it.")

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

if p is None:
    raise RuntimeError("Error initializing pipelne")

entries_prev = []

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

    for _, nnet_packet in enumerate(nnet_packets):
        entries_prev = []
        for _, e in enumerate(nnet_packet.entries()):
            if e[0]['id'] == -1.0 or e[0]['confidence'] == 0.0:
                break
            if e[0]['confidence'] > 0.5:
                entries_prev.append(e[0])

    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]

            for e in entries_prev:
                pt1 = int(e['left'] * img_w), int(e['top'] * img_h)
                pt2 = int(e['right'] * img_w), int(e['bottom'] * img_h)

                cv2.rectangle(frame, pt1, pt2, (0, 0, 255), 2)

            cv2.imshow('previewout', frame)

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

del p
depthai.deinit_device()