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- import os
- import time
- import threading
- import cv2
- import numpy as np
- from fastapi import FastAPI, HTTPException
- import uvicorn
- from depth_common import (
- Settings,
- TemporalFilter,
- compute_roi_bounds,
- extract_depth_data,
- find_nearest_point,
- init_depth_pipeline,
- nearest_distance_in_roi,
- )
- from utils import frame_to_bgr_image
- # 采样参数
- SAMPLE_COUNT = 10
- FRAME_TIMEOUT_MS = 200
- SAMPLE_TIMEOUT_SEC = 8
- MAX_SAVED_IMAGES = int(os.getenv("MAX_SAVED_IMAGES", "1000"))
- # 从环境变量加载测量配置
- SETTINGS = Settings.from_env()
- app = FastAPI(title="Cargo Height API")
- # 相机相关的全局状态(由锁保护)
- _pipeline = None
- _depth_intrinsics = None
- _temporal_filter = None
- _lock = threading.Lock()
- def _init_camera():
- # 延迟初始化相机,避免重复启动
- global _pipeline, _depth_intrinsics, _temporal_filter
- if _pipeline is not None:
- return
- try:
- pipeline, depth_intrinsics, _ = init_depth_pipeline()
- except Exception as exc:
- raise RuntimeError(f"Failed to init depth camera: {exc}") from exc
- _pipeline = pipeline
- _depth_intrinsics = depth_intrinsics
- _temporal_filter = TemporalFilter(alpha=0.5)
- def _shutdown_camera():
- # 关闭相机资源
- global _pipeline
- if _pipeline is None:
- return
- _pipeline.stop()
- _pipeline = None
- def _measure_once():
- # 单次采样:获取一帧并在 ROI 内计算最近距离
- frames = _pipeline.wait_for_frames(FRAME_TIMEOUT_MS)
- if frames is None:
- return None
- color_frame = frames.get_color_frame()
- depth_frame = frames.get_depth_frame()
- depth_data = extract_depth_data(depth_frame, SETTINGS, _temporal_filter)
- if depth_data is None:
- return None
- bounds = compute_roi_bounds(depth_data, _depth_intrinsics, SETTINGS)
- if bounds is None:
- return None
- x_start, x_end, y_start, y_end, center_distance = bounds
- roi = depth_data[y_start:y_end, x_start:x_end]
- nearest_distance = nearest_distance_in_roi(roi, SETTINGS)
- if nearest_distance is None:
- return None
- return {
- "nearest_distance": nearest_distance,
- "color_frame": color_frame,
- "depth_data": depth_data,
- "bounds": bounds,
- "center_distance": center_distance,
- }
- def _save_current_sample_images(sample):
- save_image_dir = os.path.join(os.getcwd(), "sample_images")
- os.makedirs(save_image_dir, exist_ok=True)
- now = time.localtime()
- time_str = time.strftime("%Y%m%d_%H%M%S", now)
- millis = int((time.time() % 1) * 1000)
- timestamp = f"{time_str}_{millis:03d}"
- color_frame = sample.get("color_frame")
- if color_frame is not None:
- color_image = frame_to_bgr_image(color_frame)
- if color_image is not None:
- color_height, color_width = color_image.shape[:2]
- color_file = os.path.join(
- save_image_dir,
- f"color_{color_width}x{color_height}_{timestamp}.png",
- )
- cv2.imwrite(color_file, color_image)
- depth_data = sample["depth_data"]
- x_start, x_end, y_start, y_end, center_distance = sample["bounds"]
- nearest_distance = sample["nearest_distance"]
- roi = depth_data[y_start:y_end, x_start:x_end]
- nearest_point = find_nearest_point(roi, x_start, y_start, SETTINGS, nearest_distance)
- depth_image = cv2.normalize(depth_data, None, 0, 255, cv2.NORM_MINMAX, dtype=cv2.CV_8U)
- depth_image = cv2.applyColorMap(depth_image, cv2.COLORMAP_JET)
- cv2.rectangle(
- depth_image,
- (x_start, y_start),
- (x_end - 1, y_end - 1),
- (0, 255, 0),
- 2,
- )
- if nearest_point is not None:
- cv2.circle(depth_image, nearest_point, 4, (0, 0, 0), -1)
- cv2.circle(depth_image, nearest_point, 6, (0, 255, 255), 2)
- cv2.putText(
- depth_image,
- f"nearest: {nearest_distance} mm",
- (10, 30),
- cv2.FONT_HERSHEY_SIMPLEX,
- 0.8,
- (255, 255, 255),
- 2,
- cv2.LINE_AA,
- )
- cv2.putText(
- depth_image,
- f"center: {int(center_distance)} mm",
- (10, 60),
- cv2.FONT_HERSHEY_SIMPLEX,
- 0.8,
- (255, 255, 255),
- 2,
- cv2.LINE_AA,
- )
- depth_h, depth_w = depth_image.shape[:2]
- depth_file = os.path.join(
- save_image_dir,
- f"depth_annotated_{depth_w}x{depth_h}_{timestamp}.png",
- )
- cv2.imwrite(depth_file, depth_image)
- _prune_saved_images(save_image_dir, MAX_SAVED_IMAGES)
- def _prune_saved_images(save_dir, max_images):
- png_files = [
- os.path.join(save_dir, name)
- for name in os.listdir(save_dir)
- if name.lower().endswith(".png")
- ]
- if len(png_files) <= max_images:
- return
- png_files.sort(key=os.path.getmtime)
- for file_path in png_files[: len(png_files) - max_images]:
- try:
- os.remove(file_path)
- except OSError:
- pass
- @app.on_event("startup")
- def on_startup():
- # 服务启动时初始化相机
- _init_camera()
- @app.on_event("shutdown")
- def on_shutdown():
- # 服务关闭时释放相机
- _shutdown_camera()
- @app.get("/height")
- def get_height():
- # 采集多次样本并返回中位数高度
- start_time = time.time()
- samples = []
- first_valid_sample = None
- first_color_frame = None
- with _lock:
- while len(samples) < SAMPLE_COUNT and (time.time() - start_time) < SAMPLE_TIMEOUT_SEC:
- sample = _measure_once()
- if sample is not None:
- samples.append(sample["nearest_distance"])
- if first_valid_sample is None:
- first_valid_sample = sample
- if first_color_frame is None and sample.get("color_frame") is not None:
- first_color_frame = sample.get("color_frame")
- # If no color frame arrived during valid depth sampling, try a few extra pulls.
- if first_color_frame is None:
- for _ in range(5):
- frames = _pipeline.wait_for_frames(FRAME_TIMEOUT_MS)
- if frames is None:
- continue
- color_frame = frames.get_color_frame()
- if color_frame is not None:
- first_color_frame = color_frame
- break
- if first_valid_sample is not None:
- if first_color_frame is not None:
- first_valid_sample["color_frame"] = first_color_frame
- _save_current_sample_images(first_valid_sample)
- if len(samples) < SAMPLE_COUNT:
- raise HTTPException(status_code=503, detail="Insufficient valid samples from depth camera")
- median_value = int(np.median(np.array(samples, dtype=np.int32)))
- return {
- "height_mm": median_value,
- "samples": samples,
- "unit": "mm",
- "sample_count": SAMPLE_COUNT,
- }
- @app.get("/health")
- def health():
- # 健康检查接口
- return {"status": "ok"}
- def main():
- # 读取监听地址并启动 API 服务
- host = os.getenv("API_HOST", "127.0.0.1")
- port = int(os.getenv("API_PORT", "8080"))
- uvicorn.run("api:app", host=host, port=port, log_level="info")
- if __name__ == "__main__":
- main()
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