import numpy as np
import cv2, time
import yaml
from openvino.runtime import Core

# 读取配置文件
def read_config(file_path='model/safe_det/metadata.yaml'):
    with open(file_path, 'r',encoding="utf-8") as file:
        config = yaml.safe_load(file)
    return config


MODEL_NAME = "model/best.xml"

CLASSES = read_config()['names']
colors = np.random.uniform(0, 255, size=(len(CLASSES), 3))



def draw_bounding_box(img, class_id, confidence, x, y, x_plus_w, y_plus_h):
    label = f'{CLASSES[class_id]} ({confidence:.2f})'
    color = colors[class_id]
    cv2.rectangle(img, (x, y), (x_plus_w, y_plus_h), color, 2)
    cv2.putText(img, label, (x - 10, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)


# 实例化Core对象
core = Core()
# 载入并编译模型
# 加载模型
model_path = "model/safe_det/best.xml"  # 替换为你的模型路径
model = core.read_model(model=model_path)
net = core.compile_model(model=model, device_name="CPU")
# 获得模型输出节点
output_node = net.outputs[0]  # yolov8n只有一个输出节点
ir = net.create_infer_request()
cap = cv2.VideoCapture(0)

while True:
    start = time.time()
    ret, frame = cap.read()
    if not ret:
        break
    [height, width, _] = frame.shape
    length = max((height, width))
    image = np.zeros((length, length, 3), np.uint8)
    image[0:height, 0:width] = frame
    scale = length / 640

    blob = cv2.dnn.blobFromImage(image, scalefactor=1 / 255, size=(640, 640), swapRB=True)
    outputs = ir.infer(blob)[output_node]
    outputs = np.array([cv2.transpose(outputs[0])])
    rows = outputs.shape[1]

    boxes = []
    scores = []
    class_ids = []

    for i in range(rows):
        classes_scores = outputs[0][i][4:]
        (minScore, maxScore, minClassLoc, (x, maxClassIndex)) = cv2.minMaxLoc(classes_scores)
        if maxScore >= 0.25:
            box = [outputs[0][i][0] - (0.5 * outputs[0][i][2]), outputs[0][i][1] - (0.5 * outputs[0][i][3]),
                   outputs[0][i][2], outputs[0][i][3]]
            boxes.append(box)
            scores.append(maxScore)
            class_ids.append(maxClassIndex)

    result_boxes = cv2.dnn.NMSBoxes(boxes, scores, 0.25, 0.45, 0.5)

    for i in range(len(result_boxes)):
        index = result_boxes[i]
        box = boxes[index]
        draw_bounding_box(frame, class_ids[index], scores[index], round(box[0] * scale), round(box[1] * scale),
                          round((box[0] + box[2]) * scale), round((box[1] + box[3]) * scale))
    end = time.time()
    print("start", start)
    print("end", end)
    print("time",end - start)
    # show FPS
    fps = (1 / (end - start))
    fps_label = "%.2f FPS" % fps
    cv2.putText(frame, fps_label, (10, 25), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
    cv2.imshow('YOLOv8 OpenVINO Infer Demo on AIxBoard', frame)
    # wait key for ending
    if cv2.waitKey(1) > -1:
        cap.release()
        cv2.destroyAllWindows()
        break