471 lines
20 KiB
Python
471 lines
20 KiB
Python
import os
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import time
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import json
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import argparse
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from datetime import datetime
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import cv2
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import numpy as np
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from multispectral_client import MultiSpectralClient
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with open("config.json", "r", encoding="utf-8") as f:
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config = json.load(f)
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RAW_SIZE = config.get("raw_size") # [W, H]
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MODULE_PARAMS = config.get("module_params_json")
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# =========================
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# Helpers gerais
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# =========================
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def ts_name() -> str:
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return datetime.now().strftime("%Y%m%d_%H%M%S_%f")[:-3]
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def overlay_hud(
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img_bgr: np.ndarray,
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lines: list[str],
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base_h: int = 720,
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base_font_scale: float = 0.75,
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base_line_step: int = 28,
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):
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h, w = img_bgr.shape[:2]
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scale = h / float(base_h)
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scale = max(scale, 0.4)
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font_scale = base_font_scale * scale
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line_step = int(base_line_step * scale)
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thick_outline = max(1, int(3 * scale))
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thick_text = max(1, int(2 * scale))
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y = int(24 * scale)
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x = int(12 * scale)
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for s in lines:
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cv2.putText(img_bgr, s, (x, y), cv2.FONT_HERSHEY_SIMPLEX, font_scale, (0, 0, 0), thick_outline, cv2.LINE_AA)
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cv2.putText(img_bgr, s, (x, y), cv2.FONT_HERSHEY_SIMPLEX, font_scale, (255, 255, 255), thick_text, cv2.LINE_AA)
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y += line_step
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def save_sample(
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base_dir: str,
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frame_type: str,
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preview_bgr: np.ndarray,
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meta: dict,
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raw_payload: np.ndarray | None = None,
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packed_raw: np.ndarray | None = None,
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packed_raw_by_camera: dict | None = None,
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):
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os.makedirs(base_dir, exist_ok=True)
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name = ts_name()
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png_path = os.path.join(base_dir, f"{name}.png")
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json_path = os.path.join(base_dir, f"{name}.json")
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if frame_type in ("RGB", "MULTISPEC"):
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if raw_payload is None:
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raise ValueError(f"raw_payload não pode ser None quando frame_type='{frame_type}'")
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payload_path = os.path.join(base_dir, f"{name}.raw")
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raw_payload.astype(np.float32).tofile(payload_path)
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meta["saved_payload_type"] = frame_type.lower()
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meta["saved_payload_path"] = os.path.basename(payload_path)
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meta["saved_payload_dtype"] = "float32"
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meta["saved_payload_shape"] = list(raw_payload.shape)
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elif frame_type == "RAW_BRUTO":
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if packed_raw_by_camera is not None:
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payload_files = {}
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payload_shapes = {}
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payload_dtypes = {}
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for cam_id, arr in packed_raw_by_camera.items():
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path = os.path.join(base_dir, f"{name}_{cam_id}.bin")
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arr.tofile(path)
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payload_files[cam_id] = os.path.basename(path)
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payload_shapes[cam_id] = list(arr.shape)
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payload_dtypes[cam_id] = str(arr.dtype)
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meta["saved_payload_type"] = "raw_native_multi"
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meta["saved_payload_paths"] = payload_files
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meta["saved_payload_shapes"] = payload_shapes
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meta["saved_payload_dtypes"] = payload_dtypes
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else:
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if packed_raw is None:
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raise ValueError("packed_raw não pode ser None quando frame_type='RAW_BRUTO'")
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payload_path = os.path.join(base_dir, f"{name}.bin")
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packed_raw.tofile(payload_path)
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meta["saved_payload_type"] = "raw_native_single"
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meta["saved_payload_path"] = os.path.basename(payload_path)
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meta["saved_payload_dtype"] = str(packed_raw.dtype)
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meta["saved_payload_shape"] = list(packed_raw.shape)
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else:
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raise ValueError(f"frame_type não suportado para save: {frame_type}")
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cv2.imwrite(png_path, preview_bgr)
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with open(json_path, "w", encoding="utf-8") as f:
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json.dump(meta, f, ensure_ascii=False, indent=2)
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return png_path, json_path
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def get_camera_map_from_status(status: dict) -> dict:
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result = {}
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for cam in status.get("cameras", []):
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result[cam.get("id")] = cam
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return result
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# =========================
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# MAIN
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# =========================
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def main():
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parser = argparse.ArgumentParser(
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description="Captura de dataset usando módulo multispectral Pi + StreamReceiver.",
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formatter_class=argparse.ArgumentDefaultsHelpFormatter,
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)
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parser.add_argument("--cana", required=True, choices=["baixa", "media", "alta"], help="Estado da cana no momento da coleta.")
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parser.add_argument("--horario", required=True, choices=["cedo", "meio_dia", "entardecer", "nublado"], help="Janela de iluminação / horário da coleta.")
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parser.add_argument("--out_root", default="dataset", help="Pasta raiz do dataset.")
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parser.add_argument("--pi_host", default="192.168.105.6", help="IP do servidor no Raspberry Pi.")
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parser.add_argument("--pc_host", default="192.168.105.5", help="IP local do notebook/PC que receberá o stream.")
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parser.add_argument("--stream_port", type=int, default=6001, help="Porta TCP do receiver de stream.")
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parser.add_argument("--server_port", type=int, default=5000, help="Porta TCP do servidor de comandos no Pi.")
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parser.add_argument("--fps", type=int, default=20, help="FPS desejado.")
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parser.add_argument("--width", type=int, default=RAW_SIZE[0], help="Largura óptica da câmera.")
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parser.add_argument("--height", type=int, default=RAW_SIZE[1], help="Altura óptica da câmera.")
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parser.add_argument("--interval", type=float, default=1.0, help="Intervalo em segundos para auto-save quando ligado.")
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parser.add_argument("--preview_upscale", type=int, default=2, help="Fator de upscale visual do preview.")
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parser.add_argument("--bayer", default="GBRG", choices=["GBRG", "GRBG", "RGGB", "BGGR"], help="Padrão Bayer das câmeras.")
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parser.add_argument("--output_dtype", default="float32", choices=["uint8", "uint16", "float32"], help="Dtype do payload processado no Pi.")
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parser.add_argument("--frame_type", default="RAW_BRUTO", choices=["RAW_BRUTO", "RGB", "MULTISPEC"], help="Tipo de payload pedido ao Pi.")
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parser.add_argument("--capture_mode", default="AUTO", choices=["AUTO", "SINGLE", "DOUBLE", "TRIPLE"], help="Modo de captura desejado no módulo.")
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parser.add_argument("--raw_policy", default="allow_single", choices=["allow_single", "require_triple"], help="Quando frame_type=RAW_BRUTO, define se o script aceita 1 câmera ou exige 3.")
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parser.add_argument("--module_calibration_json", default=MODULE_PARAMS, help="JSON salvo pelo calibrador de sensores com parâmetros fixos por câmera.")
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args = parser.parse_args()
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effective_capture_mode = args.capture_mode
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raw_w = args.width
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raw_h = args.height
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session_dir = os.path.join(
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args.out_root,
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"brutas",
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f"cana_{args.cana}",
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args.horario,
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datetime.now().strftime("%Y%m%d"),
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)
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os.makedirs(session_dir, exist_ok=True)
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print("============================================")
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print("Coleta de dataset - Módulo Multiespectral")
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print(f"Cana : {args.cana}")
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print(f"Horário : {args.horario}")
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print(f"Saída : {session_dir}")
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print(f"Sensor : {raw_w}x{raw_h} | Bayer={args.bayer}")
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print(f"FrameType : {args.frame_type}")
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print(f"CaptureMode : {args.capture_mode} -> efetivo={effective_capture_mode}")
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print(f"RAW policy : {args.raw_policy}")
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print("============================================")
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auto_save = False
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last_auto_t = 0.0
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preview_upscale = args.preview_upscale
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t_view_fps = time.time()
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view_frames = 0
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fps_view = 0.0
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t_stream_fps = time.time()
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last_stream_frame_id = None
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stream_frames_accum = 0
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fps_stream = 0.0
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last_msg = ""
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last_msg_t = 0.0
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window_name = "Dataset Capture (C/SPACE=save | A=auto-save | M=preview scale | Q=quit)"
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cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
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last_frame_id = -1
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last_payload_float = None
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last_packed_raw = None
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last_packed_raw_by_camera = None
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last_preview_bgr = None
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last_meta_stream = None
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try:
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with MultiSpectralClient(
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pi_host=args.pi_host,
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pc_host=args.pc_host,
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server_port=args.server_port,
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stream_port=args.stream_port,
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width=raw_w,
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height=raw_h,
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bayer=args.bayer,
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fps=args.fps,
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frame_type=args.frame_type,
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output_dtype=args.output_dtype,
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capture_mode=effective_capture_mode,
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raw_policy=args.raw_policy,
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module_calibration_json=args.module_calibration_json,
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) as cam:
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while True:
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t0 = time.time()
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frame, meta = cam.get_next_frame(timeout=1.0)
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if meta is not None and frame is not None and meta.get("frame_id") != last_frame_id:
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last_frame_id = meta["frame_id"]
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try:
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frame_type = meta.get("frame_type", "RAW_BRUTO")
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dtype_str = meta.get("dtype") or meta.get("output_dtype", "uint8")
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preview_source_id = "cam2"
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if frame_type == "RAW_BRUTO":
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if isinstance(frame, dict):
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packed_by_camera = frame
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preview_bgr, raw3_preview, preview_source_id = cam.build_preview_from_raw_payload(frame=frame, meta=meta)
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last_packed_raw = None
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last_packed_raw_by_camera = {cam_id: arr.copy() for cam_id, arr in packed_by_camera.items()}
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last_payload_float = raw3_preview.copy()
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else:
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preview_bgr, raw3_preview, preview_source_id = cam.build_preview_from_raw_payload(frame=frame, meta=meta)
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last_packed_raw = frame.copy()
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last_packed_raw_by_camera = None
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last_payload_float = raw3_preview.copy()
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elif frame_type == "RGB":
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rgb_chw = frame
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if not isinstance(rgb_chw, np.ndarray) or rgb_chw.ndim != 3:
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raise RuntimeError(f"Frame RGB inválido: type={type(rgb_chw)}")
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if dtype_str == "uint8":
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payload_float = rgb_chw.astype(np.float32) / 255.0
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elif dtype_str == "float32":
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payload_float = rgb_chw.astype(np.float32)
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elif dtype_str == "uint16":
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payload_float = rgb_chw.astype(np.float32) / 65535.0
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else:
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raise RuntimeError(f"dtype RGB não suportado: {dtype_str}")
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preview_rgb = np.transpose(payload_float, (1, 2, 0))
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preview_bgr = cv2.cvtColor(
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np.clip(preview_rgb * 255.0, 0, 255).astype(np.uint8),
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cv2.COLOR_RGB2BGR
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)
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last_payload_float = payload_float.copy()
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last_packed_raw = None
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last_packed_raw_by_camera = None
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elif frame_type == "MULTISPEC":
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multispec_chw = frame
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if not isinstance(multispec_chw, np.ndarray) or multispec_chw.ndim != 3 or multispec_chw.shape[0] not in (4, 5):
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raise RuntimeError(f"Frame MULTISPEC inválido: shape={getattr(multispec_chw, 'shape', None)}")
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if dtype_str == "uint8":
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payload_float = multispec_chw.astype(np.float32) / 255.0
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elif dtype_str == "float32":
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payload_float = multispec_chw.astype(np.float32)
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elif dtype_str == "uint16":
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payload_float = multispec_chw.astype(np.float32) / 65535.0
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else:
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raise RuntimeError(f"dtype MULTISPEC não suportado: {dtype_str}")
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preview_rgb = np.transpose(payload_float[:3], (1, 2, 0))
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preview_bgr = cv2.cvtColor(
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np.clip(preview_rgb * 255.0, 0, 255).astype(np.uint8),
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cv2.COLOR_RGB2BGR
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)
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last_payload_float = payload_float.copy()
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last_packed_raw = None
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last_packed_raw_by_camera = None
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else:
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raise RuntimeError(f"frame_type não suportado neste script: {frame_type}")
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if preview_upscale and preview_upscale > 1:
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preview_show = cv2.resize(
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preview_bgr,
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(preview_bgr.shape[1] * preview_upscale, preview_bgr.shape[0] * preview_upscale),
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interpolation=cv2.INTER_NEAREST,
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)
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else:
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preview_show = preview_bgr.copy()
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curr_frame_id = meta.get("frame_id")
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if curr_frame_id is not None:
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if last_stream_frame_id != curr_frame_id:
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stream_frames_accum += 1
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last_stream_frame_id = curr_frame_id
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dt_stream = time.time() - t_stream_fps
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if dt_stream >= 1.0:
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fps_stream = stream_frames_accum / dt_stream
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stream_frames_accum = 0
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t_stream_fps = time.time()
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view_frames += 1
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dt_view = time.time() - t_view_fps
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if dt_view >= 1.0:
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fps_view = view_frames / dt_view
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view_frames = 0
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t_view_fps = time.time()
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active_sources = meta.get("payload_sources")
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lines = [
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f"CANA: {args.cana} | HORA: {args.horario} | Pasta: {os.path.basename(session_dir)}",
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f"Type={meta.get('frame_type')} | CaptureMode={effective_capture_mode} | RAW policy={args.raw_policy}",
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f"Sources={active_sources} | FPS_STREAM={fps_stream:.1f} | FPS_VIEW={fps_view:.1f}",
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f"frame_id={meta.get('frame_id')} | layout={meta.get('output_layout')} | dtype={meta.get('dtype') or meta.get('output_dtype')}",
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f"codec={meta.get('codec_name', meta.get('codec_family', '-'))} | comp={meta.get('dt_comp', 0):.4f}s | send={meta.get('dt_send_payload_prev', 0):.4f}s",
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f"CAM_PARAMS={os.path.basename(args.module_calibration_json)} | controles fixos aplicados",
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"Keys: C/SPACE=save | A=auto-save | M=preview | Q/Esc=quit"
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]
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overlay_hud(preview_show, lines, base_h=raw_h)
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if last_msg and (time.time() - last_msg_t) < 2.0:
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cv2.putText(preview_show, last_msg, (12, preview_show.shape[0] - 18),
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cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2, cv2.LINE_AA)
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cv2.imshow(window_name, preview_show)
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last_preview_bgr = preview_bgr.copy()
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last_meta_stream = dict(meta)
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except Exception as e:
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err = np.zeros((500, 1200, 3), dtype=np.uint8)
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cv2.putText(err, f"Erro ao processar frame: {e}", (20, 60),
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cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2, cv2.LINE_AA)
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cv2.imshow(window_name, err)
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print(f"[ERRO FRAME] {e}")
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now = time.time()
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can_save = (
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last_meta_stream is not None and
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last_preview_bgr is not None and
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(
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(last_meta_stream.get("frame_type") in ("RGB", "MULTISPEC") and last_payload_float is not None) or
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(last_meta_stream.get("frame_type") == "RAW_BRUTO" and (last_packed_raw is not None or last_packed_raw_by_camera is not None))
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)
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)
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if auto_save and can_save and (now - last_auto_t) >= args.interval:
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frame_type_save = last_meta_stream.get("frame_type")
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meta_save = {
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"ts": datetime.now().isoformat(timespec="milliseconds"),
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"cana": args.cana,
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"horario": args.horario,
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"sensor_width": raw_w,
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"sensor_height": raw_h,
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"bayer_pattern": args.bayer,
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"fps_target": args.fps,
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"frame_type": frame_type_save,
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"capture_mode_requested": args.capture_mode,
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"capture_mode_effective": effective_capture_mode,
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"raw_policy": args.raw_policy,
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"stream_meta": last_meta_stream,
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"applied_camera_controls": cam.applied_camera_controls,
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"camera_params_json": args.module_calibration_json,
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"note": "autosave",
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"raw_preview_reference_camera": preview_source_id,
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}
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save_sample(
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session_dir,
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frame_type=frame_type_save,
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preview_bgr=last_preview_bgr,
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meta=meta_save,
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raw_payload=last_payload_float,
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packed_raw=last_packed_raw,
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packed_raw_by_camera=last_packed_raw_by_camera,
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)
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last_msg = "SALVO (auto)"
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last_msg_t = now
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last_auto_t = now
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k = cv2.waitKey(1) & 0xFF
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if k in (ord("q"), ord("Q"), 27):
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break
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elif k in (ord("a"), ord("A")):
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auto_save = not auto_save
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last_msg = f"AutoSave -> {'ON' if auto_save else 'OFF'}"
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last_msg_t = time.time()
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elif k in (ord("m"), ord("M")):
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preview_upscale = 0 if preview_upscale else args.preview_upscale
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last_msg = f"Preview UPSCALE -> {preview_upscale}"
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last_msg_t = time.time()
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elif k in (ord("c"), ord("C"), 32):
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if can_save:
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frame_type_save = last_meta_stream.get("frame_type")
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meta_save = {
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"ts": datetime.now().isoformat(timespec="milliseconds"),
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"cana": args.cana,
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"horario": args.horario,
|
|
"sensor_width": raw_w,
|
|
"sensor_height": raw_h,
|
|
"bayer_pattern": args.bayer,
|
|
"fps_target": args.fps,
|
|
"frame_type": frame_type_save,
|
|
"capture_mode_requested": args.capture_mode,
|
|
"capture_mode_effective": effective_capture_mode,
|
|
"raw_policy": args.raw_policy,
|
|
"stream_meta": last_meta_stream,
|
|
"applied_camera_controls": cam.applied_camera_controls,
|
|
"camera_params_json": args.module_calibration_json,
|
|
"note": "manual",
|
|
"raw_preview_reference_camera": preview_source_id,
|
|
}
|
|
|
|
save_sample(
|
|
session_dir,
|
|
frame_type=frame_type_save,
|
|
preview_bgr=last_preview_bgr,
|
|
meta=meta_save,
|
|
raw_payload=last_payload_float,
|
|
packed_raw=last_packed_raw,
|
|
packed_raw_by_camera=last_packed_raw_by_camera,
|
|
)
|
|
|
|
last_msg = "SALVO (manual)"
|
|
last_msg_t = time.time()
|
|
|
|
dt_loop = time.time() - t0
|
|
if dt_loop < 0.001:
|
|
time.sleep(0.001)
|
|
|
|
finally:
|
|
cv2.destroyAllWindows()
|
|
print("Fim da captura.")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main() |