import os import time import json import argparse from datetime import datetime import cv2 import numpy as np from core.oak_fcc3_client import OakFcc3Client as MultiSpectralClient with open("config.json", "r", encoding="utf-8") as f: config = json.load(f) RAW_SIZE = config.get("raw_size") # [W, H] MODULE_PARAMS = config.get("module_params_json") # ========================= # Helpers gerais # ========================= def ts_name() -> str: return datetime.now().strftime("%Y%m%d_%H%M%S_%f")[:-3] def overlay_hud( img_bgr: np.ndarray, lines: list[str], base_h: int = 720, base_font_scale: float = 0.75, base_line_step: int = 28, ): h, w = img_bgr.shape[:2] scale = h / float(base_h) scale = max(scale, 0.4) font_scale = base_font_scale * scale line_step = int(base_line_step * scale) thick_outline = max(1, int(3 * scale)) thick_text = max(1, int(2 * scale)) y = int(24 * scale) x = int(12 * scale) for s in lines: cv2.putText(img_bgr, s, (x, y), cv2.FONT_HERSHEY_SIMPLEX, font_scale, (0, 0, 0), thick_outline, cv2.LINE_AA) cv2.putText(img_bgr, s, (x, y), cv2.FONT_HERSHEY_SIMPLEX, font_scale, (255, 255, 255), thick_text, cv2.LINE_AA) y += line_step def save_sample( base_dir: str, frame_type: str, preview_bgr: np.ndarray, meta: dict, raw_payload: np.ndarray | None = None, packed_raw: np.ndarray | None = None, packed_raw_by_camera: dict | None = None, ): os.makedirs(base_dir, exist_ok=True) name = ts_name() png_path = os.path.join(base_dir, f"{name}.png") json_path = os.path.join(base_dir, f"{name}.json") if frame_type in ("RGB", "MULTISPEC"): if raw_payload is None: raise ValueError(f"raw_payload não pode ser None quando frame_type='{frame_type}'") payload_path = os.path.join(base_dir, f"{name}.raw") raw_payload.astype(np.float32).tofile(payload_path) meta["saved_payload_type"] = frame_type.lower() meta["saved_payload_path"] = os.path.basename(payload_path) meta["saved_payload_dtype"] = "float32" meta["saved_payload_shape"] = list(raw_payload.shape) elif frame_type == "RAW_BRUTO": if packed_raw_by_camera is not None: payload_files = {} payload_shapes = {} payload_dtypes = {} for cam_id, arr in packed_raw_by_camera.items(): path = os.path.join(base_dir, f"{name}_{cam_id}.bin") arr.tofile(path) payload_files[cam_id] = os.path.basename(path) payload_shapes[cam_id] = list(arr.shape) payload_dtypes[cam_id] = str(arr.dtype) meta["saved_payload_type"] = "raw_native_multi" meta["saved_payload_paths"] = payload_files meta["saved_payload_shapes"] = payload_shapes meta["saved_payload_dtypes"] = payload_dtypes else: if packed_raw is None: raise ValueError("packed_raw não pode ser None quando frame_type='RAW_BRUTO'") payload_path = os.path.join(base_dir, f"{name}.bin") packed_raw.tofile(payload_path) meta["saved_payload_type"] = "raw_native_single" meta["saved_payload_path"] = os.path.basename(payload_path) meta["saved_payload_dtype"] = str(packed_raw.dtype) meta["saved_payload_shape"] = list(packed_raw.shape) else: raise ValueError(f"frame_type não suportado para save: {frame_type}") cv2.imwrite(png_path, preview_bgr) with open(json_path, "w", encoding="utf-8") as f: json.dump(meta, f, ensure_ascii=False, indent=2) return png_path, json_path def get_camera_map_from_status(status: dict) -> dict: result = {} for cam in status.get("cameras", []): result[cam.get("id")] = cam return result # ========================= # MAIN # ========================= def main(): parser = argparse.ArgumentParser( description="Captura de dataset usando módulo multispectral Pi + StreamReceiver.", formatter_class=argparse.ArgumentDefaultsHelpFormatter, ) parser.add_argument("--cana", required=True, choices=["baixa", "media", "alta"], help="Estado da cana no momento da coleta.") parser.add_argument("--horario", required=True, choices=["cedo", "meio_dia", "entardecer", "nublado"], help="Janela de iluminação / horário da coleta.") parser.add_argument("--out_root", default="dataset", help="Pasta raiz do dataset.") parser.add_argument("--fps", type=int, default=20, help="FPS desejado.") parser.add_argument("--width", type=int, default=RAW_SIZE[0], help="Largura óptica da câmera.") parser.add_argument("--height", type=int, default=RAW_SIZE[1], help="Altura óptica da câmera.") parser.add_argument("--interval", type=float, default=1.0, help="Intervalo em segundos para auto-save quando ligado.") parser.add_argument("--preview_upscale", type=int, default=2, help="Fator de upscale visual do preview.") parser.add_argument("--bayer", default="RGGB", choices=["GBRG", "GRBG", "RGGB", "BGGR"], help="Padrão Bayer das câmeras.") parser.add_argument("--output_dtype", default="float32", choices=["uint8", "uint16", "float32"], help="Dtype do payload processado no Pi.") parser.add_argument("--frame_type", default="RAW_BRUTO", choices=["RAW_BRUTO", "RGB", "MULTISPEC"], help="Tipo de payload pedido ao Pi.") parser.add_argument("--capture_mode", default="AUTO", choices=["AUTO", "SINGLE", "DOUBLE", "TRIPLE"], help="Modo de captura desejado no módulo.") 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.") parser.add_argument("--module_calibration_json", default=MODULE_PARAMS, help="JSON salvo pelo calibrador de sensores com parâmetros fixos por câmera.") args = parser.parse_args() effective_capture_mode = args.capture_mode raw_w = args.width raw_h = args.height session_dir = os.path.join( args.out_root, "brutas", f"cana_{args.cana}", args.horario, datetime.now().strftime("%Y%m%d"), ) os.makedirs(session_dir, exist_ok=True) print("============================================") print("Coleta de dataset - Módulo Multiespectral") print(f"Cana : {args.cana}") print(f"Horário : {args.horario}") print(f"Saída : {session_dir}") print(f"Sensor : {raw_w}x{raw_h} | Bayer={args.bayer}") print(f"FrameType : {args.frame_type}") print(f"CaptureMode : {args.capture_mode} -> efetivo={effective_capture_mode}") print(f"RAW policy : {args.raw_policy}") print("============================================") beauty_preview = False radiometric_ae = True auto_save = False last_auto_t = 0.0 preview_upscale = args.preview_upscale t_view_fps = time.time() view_frames = 0 fps_view = 0.0 t_stream_fps = time.time() last_stream_frame_id = None stream_frames_accum = 0 fps_stream = 0.0 last_msg = "" last_msg_t = 0.0 window_name = "Dataset Capture (C/SPACE=save | A=auto-save | M=preview | R=rad | Q=quit)" cv2.namedWindow(window_name, cv2.WINDOW_NORMAL) last_frame_id = -1 last_payload_float = None last_packed_raw = None last_packed_raw_by_camera = None last_preview_bgr = None last_meta_stream = None try: with MultiSpectralClient( width=raw_w, height=raw_h, bayer=args.bayer, fps=args.fps, frame_type=args.frame_type, output_dtype=args.output_dtype, capture_mode=effective_capture_mode, raw_policy=args.raw_policy, module_calibration_json=args.module_calibration_json, ) as cam: while True: t0 = time.time() frame, meta, decoded = cam.get_next_decoded(timeout=1.0) if meta is not None and frame is not None and meta.get("frame_id") != last_frame_id: last_frame_id = meta["frame_id"] try: frame_type = meta.get("frame_type", "RAW_BRUTO") dtype_str = meta.get("dtype") or meta.get("output_dtype", "uint8") preview_source_id = "rgb" if frame_type == "RAW_BRUTO": if isinstance(frame, dict): packed_by_camera = frame preview_bgr, raw3_preview, preview_source_id = cam.build_preview_from_raw_payload(frame=frame, meta=meta) if beauty_preview: rgb_preview = None previews = cam.build_visual_preview_from_raw(frame, meta) camera_info = meta.get("camera_info", {}) or {} for cam_id, img in previews.items(): role = camera_info.get(cam_id, {}).get("role") if role == "rgb": rgb_preview = img preview_source_id = cam_id break if rgb_preview is not None: preview_bgr = rgb_preview last_packed_raw = None last_packed_raw_by_camera = {cam_id: arr.copy() for cam_id, arr in packed_by_camera.items()} last_payload_float = raw3_preview.copy() elif frame_type == "RGB": rgb_chw = frame if not isinstance(rgb_chw, np.ndarray) or rgb_chw.ndim != 3: raise RuntimeError(f"Frame RGB inválido: type={type(rgb_chw)}") if dtype_str == "uint8": payload_float = rgb_chw.astype(np.float32) / 255.0 elif dtype_str == "float32": payload_float = rgb_chw.astype(np.float32) elif dtype_str == "uint16": payload_float = rgb_chw.astype(np.float32) / 65535.0 else: raise RuntimeError(f"dtype RGB não suportado: {dtype_str}") preview_rgb = np.transpose(payload_float, (1, 2, 0)) preview_bgr = cv2.cvtColor( np.clip(preview_rgb * 255.0, 0, 255).astype(np.uint8), cv2.COLOR_RGB2BGR ) last_payload_float = payload_float.copy() last_packed_raw = None last_packed_raw_by_camera = None elif frame_type == "MULTISPEC": multispec_chw = frame if not isinstance(multispec_chw, np.ndarray) or multispec_chw.ndim != 3 or multispec_chw.shape[0] not in (4, 5): raise RuntimeError(f"Frame MULTISPEC inválido: shape={getattr(multispec_chw, 'shape', None)}") if dtype_str == "uint8": payload_float = multispec_chw.astype(np.float32) / 255.0 elif dtype_str == "float32": payload_float = multispec_chw.astype(np.float32) elif dtype_str == "uint16": payload_float = multispec_chw.astype(np.float32) / 65535.0 else: raise RuntimeError(f"dtype MULTISPEC não suportado: {dtype_str}") preview_rgb = np.transpose(payload_float[:3], (1, 2, 0)) preview_bgr = cv2.cvtColor( np.clip(preview_rgb * 255.0, 0, 255).astype(np.uint8), cv2.COLOR_RGB2BGR ) last_payload_float = payload_float.copy() last_packed_raw = None last_packed_raw_by_camera = None else: raise RuntimeError(f"frame_type não suportado neste script: {frame_type}") if preview_upscale and preview_upscale > 1: preview_show = cv2.resize( preview_bgr, (preview_bgr.shape[1] * preview_upscale, preview_bgr.shape[0] * preview_upscale), interpolation=cv2.INTER_NEAREST, ) else: preview_show = preview_bgr.copy() curr_frame_id = meta.get("frame_id") if curr_frame_id is not None: if last_stream_frame_id != curr_frame_id: stream_frames_accum += 1 last_stream_frame_id = curr_frame_id dt_stream = time.time() - t_stream_fps if dt_stream >= 1.0: fps_stream = stream_frames_accum / dt_stream stream_frames_accum = 0 t_stream_fps = time.time() view_frames += 1 dt_view = time.time() - t_view_fps if dt_view >= 1.0: fps_view = view_frames / dt_view view_frames = 0 t_view_fps = time.time() active_sources = meta.get("payload_sources") rad = getattr(cam, "radiometric_controller", None) if rad and rad.enabled: st = rad.state line_rad = ( f"RAD | " f"RGB(exp={st['rgb']['exp']}, g={st['rgb']['gain']:.2f}) | " f"RE(exp={st['re']['exp']}, g={st['re']['gain']:.2f}) | " f"NIR(exp={st['nir']['exp']}, g={st['nir']['gain']:.2f})" ) else: line_rad = "RAD | OFF" lines = [ f"CANA: {args.cana} | HORA: {args.horario} | Pasta: {os.path.basename(session_dir)}", f"Type={meta.get('frame_type')} | CaptureMode={effective_capture_mode} | RAW policy={args.raw_policy}", f"Sources={active_sources} | FPS_STREAM={fps_stream:.1f} | FPS_VIEW={fps_view:.1f}", f"frame_id={meta.get('frame_id')} | layout={meta.get('output_layout')} | dtype={meta.get('dtype') or meta.get('output_dtype')}", 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", f"CAM_PARAMS={os.path.basename(args.module_calibration_json)} | controles fixos aplicados", line_rad, "Keys: C/SPACE=save | A=auto-save | M=preview | R=rad | Q/Esc=quit" ] overlay_hud(preview_show, lines, base_h=raw_h) if last_msg and (time.time() - last_msg_t) < 2.0: cv2.putText(preview_show, last_msg, (12, preview_show.shape[0] - 18), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2, cv2.LINE_AA) cv2.imshow(window_name, preview_show) last_preview_bgr = preview_bgr.copy() last_meta_stream = dict(meta) except Exception as e: err = np.zeros((500, 1200, 3), dtype=np.uint8) cv2.putText(err, f"Erro ao processar frame: {e}", (20, 60), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2, cv2.LINE_AA) cv2.imshow(window_name, err) print(f"[ERRO FRAME] {e}") now = time.time() can_save = ( last_meta_stream is not None and last_preview_bgr is not None and ( (last_meta_stream.get("frame_type") in ("RGB", "MULTISPEC") and last_payload_float is not None) or (last_meta_stream.get("frame_type") == "RAW_BRUTO" and (last_packed_raw is not None or last_packed_raw_by_camera is not None)) ) ) if auto_save and can_save and (now - last_auto_t) >= args.interval: frame_type_save = last_meta_stream.get("frame_type") meta_save = { "ts": datetime.now().isoformat(timespec="milliseconds"), "cana": args.cana, "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, "startup_camera_controls": cam.applied_camera_controls, "actual_camera_controls": cam.get_current_camera_controls(), "radiometric_last_result": cam.get_radiometric_last_result(), "camera_params_json": args.module_calibration_json, "note": "autosave", "raw_preview_reference_camera": preview_source_id, "patch_normalization_result": cam.get_last_patch_normalization_result() } 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 (auto)" last_msg_t = now last_auto_t = now k = cv2.waitKey(1) & 0xFF if k in (ord("q"), ord("Q"), 27): break elif k in (ord("a"), ord("A")): auto_save = not auto_save last_msg = f"AutoSave -> {'ON' if auto_save else 'OFF'}" last_msg_t = time.time() elif k in (ord("m"), ord("M")): #preview_upscale = 0 if preview_upscale else args.preview_upscale beauty_preview = False if beauty_preview else True last_msg = f"Preview Beauty -> {beauty_preview}" last_msg_t = time.time() elif k in (ord("r"), ord("R")): rad = getattr(cam, "radiometric_controller", None) if rad is not None: radiometric_ae = False if radiometric_ae else True rad.enabled = radiometric_ae last_msg = f"RAD -> {radiometric_ae}" last_msg_t = time.time() elif k in (ord("c"), ord("C"), 32): if can_save: frame_type_save = last_meta_stream.get("frame_type") meta_save = { "ts": datetime.now().isoformat(timespec="milliseconds"), "cana": args.cana, "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, "startup_camera_controls": cam.applied_camera_controls, "actual_camera_controls": cam.get_current_camera_controls(), "radiometric_last_result": cam.get_radiometric_last_result(), "camera_params_json": args.module_calibration_json, "note": "manual", "raw_preview_reference_camera": preview_source_id, "patch_normalization_result": cam.get_last_patch_normalization_result() } 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()