ajustes no modulo multiespectral oak-fcc-3

This commit is contained in:
Diego Freitas 2026-05-05 14:39:58 -03:00
parent 39be40aec2
commit f0f175d751
13 changed files with 984 additions and 825 deletions

View File

@ -144,13 +144,12 @@ def main():
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="GBRG", choices=["GBRG", "GRBG", "RGGB", "BGGR"], help="Padrão Bayer das câmeras.")
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.")
parser.add_argument("--radiometric_ae", action="store_true", help="Liga controle automatico de exposicao radiometrico")
args = parser.parse_args()
@ -179,6 +178,8 @@ def main():
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
@ -195,7 +196,7 @@ def main():
last_msg = ""
last_msg_t = 0.0
window_name = "Dataset Capture (C/SPACE=save | A=auto-save | M=preview scale | Q=quit)"
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
@ -215,8 +216,8 @@ def main():
output_dtype=args.output_dtype,
capture_mode=effective_capture_mode,
raw_policy=args.raw_policy,
#module_calibration_json=args.module_calibration_json,
radiometric_enabled=args.radiometric_ae,
module_calibration_json=args.module_calibration_json,
radiometric_enabled=radiometric_ae,
) as cam:
while True:
t0 = time.time()
@ -227,7 +228,7 @@ def main():
try:
frame_type = meta.get("frame_type", "RAW_BRUTO")
dtype_str = meta.get("dtype") or meta.get("output_dtype", "uint8")
preview_source_id = "cam2"
preview_source_id = "rgb"
if frame_type == "RAW_BRUTO":
if isinstance(frame, dict):
@ -235,16 +236,22 @@ def main():
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()
else:
preview_bgr, raw3_preview, preview_source_id = cam.build_preview_from_raw_payload(frame=frame, meta=meta)
last_packed_raw = frame.copy()
last_packed_raw_by_camera = None
last_payload_float = raw3_preview.copy()
elif frame_type == "RGB":
rgb_chw = frame
@ -334,9 +341,9 @@ def main():
st = rad.state
line_rad = (
f"RAD | "
f"RGB(exp={st['cam2']['exp']}, g={st['cam2']['gain']:.2f}) | "
f"RE(exp={st['cam0']['exp']}, g={st['cam0']['gain']:.2f}) | "
f"NIR(exp={st['cam1']['exp']}, g={st['cam1']['gain']:.2f})"
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"
@ -349,7 +356,7 @@ def main():
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 | Q/Esc=quit"
"Keys: C/SPACE=save | A=auto-save | M=preview | R=rad | Q/Esc=quit"
]
overlay_hud(preview_show, lines, base_h=raw_h)
@ -425,10 +432,19 @@ def main():
last_msg_t = time.time()
elif k in (ord("m"), ord("M")):
preview_upscale = 0 if preview_upscale else args.preview_upscale
last_msg = f"Preview UPSCALE -> {preview_upscale}"
#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")):
radiometric_ae = False if radiometric_ae else True
rad = getattr(cam, "radiometric_controller", None)
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")

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@ -1,34 +1,31 @@
{
"schema": "manual_multispec_offsets_v1",
"saved_at": "2026-05-04 20:50:02",
"pi_host": "192.168.105.6",
"pc_host": "192.168.105.5",
"stream_port": 6001,
"schema": "manual_multispec_offsets_v2",
"saved_at": "2026-05-05 12:39:55",
"frame_type": "RAW_BRUTO",
"capture_mode_requested": "AUTO",
"capture_mode_effective": "AUTO",
"raw_policy": "allow_single",
"sensor_width": 640,
"sensor_height": 480,
"bayer_pattern": "GBRG",
"reference_camera": "cam2",
"bayer_pattern": "RGGB",
"reference_camera": "rgb",
"baseline_mm": 75.0,
"alignment_mode": "manual_affine",
"manual_offsets": {
"cam0": {
"dx": -28,
"dy": 9,
"re": {
"dx": -8,
"dy": 39,
"theta_deg": 0.0
},
"cam1": {
"dx": -4,
"dy": 31,
"nir": {
"dx": -2,
"dy": 18,
"theta_deg": 0.0
}
},
"homographies": {
"cam0_to_cam2": null,
"cam1_to_cam2": null
"re_to_rgb": null,
"nir_to_rgb": null
},
"notes": ""
}

View File

@ -1,58 +1,58 @@
{
"schema": "multispec_module_params_v1",
"saved_at": "2026-05-05 08:03:18",
"schema": "multispec_module_params_v2",
"saved_at": "2026-05-05 13:57:20",
"frame_type": "RAW_BRUTO",
"capture_mode_requested": "AUTO",
"capture_mode_effective": "AUTO",
"raw_policy": "allow_single",
"sensor_width": 640,
"sensor_height": 480,
"bayer_pattern": "GBRG",
"bayer_pattern": "RGGB",
"camera_settings": {
"cam0": {
"rgb": {
"ae_enable": false,
"awb_enable": false,
"exposure_time_us": 15000,
"analogue_gain": 1.0,
"colour_gains": null
},
"cam1": {
"ae_enable": false,
"awb_enable": false,
"exposure_time_us": 15000,
"analogue_gain": 1.0,
"colour_gains": null
},
"cam2": {
"ae_enable": true,
"awb_enable": true,
"exposure_time_us": 15000,
"analogue_gain": 1.0,
"exposure_time_us": 20000,
"analogue_gain": 1.2100000000000002,
"colour_gains": [
1.0,
1.0
]
},
"re": {
"ae_enable": false,
"awb_enable": false,
"exposure_time_us": 20000,
"analogue_gain": 1.0,
"colour_gains": null
},
"nir": {
"ae_enable": false,
"awb_enable": false,
"exposure_time_us": 20000,
"analogue_gain": 1.0,
"colour_gains": null
}
},
"fusion_config": {
"alignment_mode": "manual_affine",
"baseline_mm": 75.0,
"reference_camera": "cam2",
"reference_camera": "rgb",
"manual_offsets": {
"cam0": {
"dx": -28,
"dy": 9,
"re": {
"dx": -8,
"dy": 39,
"theta_deg": 0.0
},
"cam1": {
"dx": -4,
"dy": 31,
"nir": {
"dx": -2,
"dy": 18,
"theta_deg": 0.0
}
},
"homographies": {
"cam0_to_cam2": null,
"cam1_to_cam2": null
"re_to_rgb": null,
"nir_to_rgb": null
},
"crop_valid_common": true,
"resize_after_crop": true,
@ -74,5 +74,13 @@
"verbose": true,
"exp_apply_threshold_us": 50,
"gain_apply_threshold": 0.02
},
"rgb_calibration": {
"enabled": true,
"gains": {
"R": 1.3000000000000003,
"G": 1.0,
"B": 1.5500000000000005
}
}
}

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@ -1,211 +1,51 @@
{
"schema": "multispec_camera_params_v1",
"saved_at": "2026-05-04 19:29:24",
"pi_host": "192.168.105.6",
"pc_host": "192.168.105.5",
"stream_port": 6001,
"schema": "multispec_camera_params_v2",
"saved_at": "2026-05-05 13:53:08",
"frame_type": "RAW_BRUTO",
"capture_mode_requested": "AUTO",
"capture_mode_effective": "AUTO",
"raw_policy": "allow_single",
"sensor_width": 640,
"sensor_height": 480,
"bayer_pattern": "GBRG",
"bayer_pattern": "RGGB",
"camera_settings": {
"cam0": {
"rgb": {
"ae_enable": false,
"awb_enable": false,
"exposure_time_us": 15000,
"analogue_gain": 1.0,
"colour_gains": null
},
"cam1": {
"ae_enable": false,
"awb_enable": false,
"exposure_time_us": 15000,
"analogue_gain": 1.0,
"colour_gains": null
},
"cam2": {
"ae_enable": true,
"awb_enable": true,
"exposure_time_us": 15000,
"analogue_gain": 1.0,
"exposure_time_us": 20000,
"analogue_gain": 1.2100000000000002,
"colour_gains": [
1.0,
1.0
]
},
"re": {
"ae_enable": false,
"awb_enable": false,
"exposure_time_us": 20000,
"analogue_gain": 1.0,
"colour_gains": null
},
"nir": {
"ae_enable": false,
"awb_enable": false,
"exposure_time_us": 20000,
"analogue_gain": 1.0,
"colour_gains": null
}
},
"rgb_calibration": {
"enabled": true,
"gains": {
"R": 1.3000000000000003,
"G": 1.0,
"B": 1.5500000000000005
}
},
"rois": {
"cam2": [
{
"name": "mesa",
"type": "polygon",
"points": [
[
429,
305
],
[
446,
195
],
[
512,
199
],
[
512,
309
]
],
"color": [
0,
255,
255
]
},
{
"name": "teto",
"type": "polygon",
"points": [
[
148,
345
],
[
153,
269
],
[
216,
265
],
[
221,
345
]
],
"color": [
0,
255,
0
]
}
],
"cam0": [
{
"name": "mesa",
"type": "polygon",
"points": [
[
417,
235
],
[
433,
158
],
[
485,
162
],
[
479,
237
]
],
"color": [
0,
255,
255
]
},
{
"name": "tet",
"type": "polygon",
"points": [
[
218,
306
],
[
219,
230
],
[
274,
225
],
[
276,
305
]
],
"color": [
0,
255,
0
]
}
],
"cam1": [
{
"name": "mesa",
"type": "polygon",
"points": [
[
468,
227
],
[
480,
123
],
[
556,
137
],
[
549,
233
]
],
"color": [
0,
255,
255
]
},
{
"name": "teto",
"type": "polygon",
"points": [
[
139,
333
],
[
157,
238
],
[
237,
258
],
[
222,
351
]
],
"color": [
0,
255,
0
]
}
]
"rgb": [],
"re": [],
"nir": []
},
"snapshots": [],
"notes": "",

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@ -1,20 +1,20 @@
{
"camera": "oak-fcc-3",
"modelo": "segformer_b1",
"model_name": "pulv_mit",
"model_name": "oak_mit",
"dual_head": false,
"main_class_name": "cana",
"es_classes": "",
"model_to_use": "geral",
"raw_size": [640, 480],
"resolucao": [1024, 800],
"raw_size": [1280, 800],
"resolucao": [1024, 640],
"roi_inicio": 0.0,
"roi_tamanho": 1.0,
"shaves": 3,
"channels": 4,
"channels": 5,
"use_ndvi": false,
"backbone": "nvidia/mit-b1",
"fusion_mode": "stacked",
"stats_source_tag": "stacked_raw4",
"stats_source_tag": "stacked_raw5",
"module_params_json": "calibration/module_params.json"
}

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@ -14,7 +14,7 @@ class OakFcc3Client:
self,
width=640,
height=400,
bayer="GBRG",
bayer="RGGB",
fps=30,
frame_type="RAW_BRUTO",
output_dtype="uint8",
@ -196,6 +196,32 @@ class OakFcc3Client:
return frame, meta, decoded
def get_next_tensor_preview(self, timeout=2.0):
frame, meta, decoded = self.get_next_decoded(timeout=timeout)
frame_type = str(meta.get("frame_type", self.frame_type)).upper()
if frame_type == "RGB":
rgb_hwc = np.transpose(frame[:3], (1, 2, 0))
preview = self._rgb01_to_bgr(rgb_hwc)
return {"rgb_tensor": preview}, meta
if frame_type == "MULTISPEC":
rgb_hwc = np.transpose(frame[:3], (1, 2, 0))
re01 = frame[3]
nir01 = frame[4]
return {
"rgb_tensor": self._rgb01_to_bgr(rgb_hwc),
"re_tensor": self._gray01_to_bgr(re01),
"nir_tensor": self._gray01_to_bgr(nir01),
}, meta
else:
return self.build_visual_preview_from_raw(frame, meta), meta
raise RuntimeError(f"frame_type não suportado para preview: {frame_type}")
def get_next_preview(self, timeout=2.0):
raw_frame, raw_meta = self.get_next_raw_frame(timeout=timeout)
@ -259,7 +285,7 @@ class OakFcc3Client:
return np.ascontiguousarray(tensor.astype(np.float32, copy=False))
def build_multispec_tensor(self, decoded, meta=None):
tensor = self.core.fuse_multispec_cameras(
tensor = self.build_infer_tensor_from_decoded(
decoded=decoded,
meta=meta,
channels_expected=5,

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@ -26,6 +26,14 @@ class RawProcessorCore:
"resize_after_crop": True,
"target_size": None,
}
self.rgb_calibration = {
"enabled": False,
"gains": {
"R": 1.0,
"G": 1.0,
"B": 1.0
}
}
if calibration_json_path:
self.load_fusion_config_json(calibration_json_path)
@ -103,10 +111,10 @@ class RawProcessorCore:
b = raw16[1::2, 0::2]
g2 = raw16[1::2, 1::2]
elif p == "RGGB":
r = raw16[0::2, 0::2]
b = raw16[0::2, 0::2]
g1 = raw16[0::2, 1::2]
g2 = raw16[1::2, 0::2]
b = raw16[1::2, 1::2]
r = raw16[1::2, 1::2]
elif p == "BGGR":
b = raw16[0::2, 0::2]
g1 = raw16[0::2, 1::2]
@ -131,6 +139,13 @@ class RawProcessorCore:
g = ((ch["G1"].astype(np.float32) + ch["G2"].astype(np.float32)) * 0.5) / max_val
b = ch["B"].astype(np.float32) / max_val
rgb_cal = getattr(self, "rgb_calibration", {}) or {}
if rgb_cal.get("enabled", False):
gains = rgb_cal.get("gains", {}) or {}
r *= float(gains.get("R", 1.0))
g *= float(gains.get("G", 1.0))
b *= float(gains.get("B", 1.0))
chw = np.stack([r, g, b], axis=0).astype(np.float32)
chw = np.clip(chw, 0.0, 1.0)
@ -823,11 +838,14 @@ class RawProcessorCore:
data = json.load(f)
fusion = data.get("fusion_config")
if not isinstance(fusion, dict):
if isinstance(fusion, dict):
self.fusion_config = self._merge_fusion_config(self.fusion_config, fusion)
else:
print("[WARN] JSON sem fusion_config. Mantendo config padrão.")
return
self.fusion_config = self._merge_fusion_config(self.fusion_config, fusion)
rgb_cal = data.get("rgb_calibration")
if isinstance(rgb_cal, dict):
self.rgb_calibration = self._merge_fusion_config(self.rgb_calibration, rgb_cal)
def _merge_fusion_config(self, default_cfg: dict, loaded_cfg: dict) -> dict:
cfg = json.loads(json.dumps(default_cfg))

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@ -44,14 +44,15 @@ class RawProcessorPreview:
def _debayer_code(self):
mapping = {
# Mapeamento ajustado para OpenCV gerar BGR correto a partir do padrão Bayer informado.
"GBRG": cv2.COLOR_BayerGR2BGR,
"GRBG": cv2.COLOR_BayerGB2BGR,
"RGGB": cv2.COLOR_BayerBG2BGR,
"BGGR": cv2.COLOR_BayerRG2BGR,
"GBRG": cv2.COLOR_BayerGB2BGR,
"GRBG": cv2.COLOR_BayerGR2BGR,
"RGGB": cv2.COLOR_BayerRG2BGR,
"BGGR": cv2.COLOR_BayerBG2BGR,
}
if self.bayer_pattern not in mapping:
raise ValueError(f"Padrão Bayer não suportado: {self.bayer_pattern}")
return mapping[self.bayer_pattern]
def apply_preview_white_balance(self, bgr: np.ndarray, strength: float = 1.0) -> np.ndarray:

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@ -10,16 +10,16 @@ with OakFcc3Client(
frame_type="RAW_BRUTO",
output_dtype="uint8",
capture_mode="AUTO",
raw_policy="require_triple",
raw_policy="allow_single",
sync_mode="best",
sync_tolerance_ms=25.0,
#module_calibration_json="calibration/module_params.json",
#radiometric_enabled=False
module_calibration_json="calibration/module_params.json",
radiometric_enabled=False
) as cam:
print("STATUS:", cam.get_status())
while True:
previews, meta = cam.get_next_preview(timeout=2.0)
previews, meta = cam.get_next_tensor_preview(timeout=2.0)
print(
"frame_id:", meta["frame_id"],
@ -28,14 +28,14 @@ with OakFcc3Client(
"sync_ok:", meta.get("sync_ok"),
)
camera_info = meta.get("camera_info", {}) or {}
title_map = {
"rgb_tensor": "RGB (tensor final)",
"re_tensor": "RE (tensor final)",
"nir_tensor": "NIR (tensor final)",
}
for cam_id, preview in previews.items():
info = camera_info.get(cam_id, {}) or {}
role = info.get("role", "unknown")
sensor = info.get("sensor", "")
title = f"{cam_id} | {role.upper()} | {sensor}"
for name, preview in previews.items():
title = title_map.get(name, name)
cv2.imshow(title, preview)
if cv2.waitKey(1) in (27, ord("q")):

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@ -27,10 +27,31 @@ def main():
if args.radiometric_json:
radiometric_data = load_json(args.radiometric_json)
# =========================
# CAMERA SETTINGS
# =========================
camera_settings = cam_data.get("camera_settings")
if not isinstance(camera_settings, dict):
raise RuntimeError("camera_json sem camera_settings válido")
# =========================
# RGB CALIBRATION (NOVO)
# =========================
rgb_calibration = cam_data.get("rgb_calibration")
if not isinstance(rgb_calibration, dict):
rgb_calibration = {
"enabled": False,
"gains": {
"R": 1.0,
"G": 1.0,
"B": 1.0,
}
}
# =========================
# RADIOMETRIC
# =========================
radiometric_config = radiometric_data.get("radiometric_config")
if not isinstance(radiometric_config, dict):
@ -55,10 +76,16 @@ def main():
"gain_apply_threshold": 0.02,
}
# =========================
# FUSION CONFIG
# =========================
fusion_config = {
"alignment_mode": fusion_data.get("alignment_mode", "manual_affine"),
"baseline_mm": fusion_data.get("baseline_mm", 75.0),
"reference_camera": fusion_data.get("reference_camera", "cam2"),
# 🔥 AJUSTE IMPORTANTE
"reference_camera": fusion_data.get("reference_camera", "rgb"),
"manual_offsets": fusion_data.get("manual_offsets", {}),
"homographies": fusion_data.get("homographies", {}),
"crop_valid_common": fusion_data.get("crop_valid_common", True),
@ -66,8 +93,11 @@ def main():
"target_size": fusion_data.get("target_size", None),
}
# =========================
# MODULE PARAMS FINAL
# =========================
module_params = {
"schema": "multispec_module_params_v1",
"schema": "multispec_module_params_v2", # 👈 versão nova
"saved_at": now_str(),
"frame_type": cam_data.get("frame_type", fusion_data.get("frame_type", "RAW_BRUTO")),
@ -79,9 +109,11 @@ def main():
"sensor_height": cam_data.get("sensor_height", fusion_data.get("sensor_height")),
"bayer_pattern": cam_data.get("bayer_pattern", fusion_data.get("bayer_pattern", "GBRG")),
# 🔥 BLOCOS PRINCIPAIS
"camera_settings": camera_settings,
"fusion_config": fusion_config,
"radiometric_config": radiometric_config,
"rgb_calibration": rgb_calibration, # 👈 NOVO
}
with open(args.out, "w", encoding="utf-8") as f:

View File

@ -61,7 +61,7 @@ def build_visual_from_saved_payload(payload_path: Path, meta: dict, cam_id: str
# Busca metadados da câmera no stream_meta
stream_meta = meta.get("stream_meta", {}) or {}
cam_frames = stream_meta.get("camera_frames", {}) or {}
cam_frames = stream_meta.get("camera_info", {}) or {}
cam_meta = cam_frames.get(cam_id, {}) or {}
role = cam_meta.get("role", cam_id)
@ -133,7 +133,7 @@ def build_visual_from_saved_payload(payload_path: Path, meta: dict, cam_id: str
raise RuntimeError(f"Payload MULTISPEC inválido, shape={arr.shape}")
rgb_hwc = chw_to_hwc(arr[:3].astype(np.float32))
preview_bgr = normalize_float01_to_bgr(rgb_hwc)
rgb_bgr = normalize_float01_to_bgr(rgb_hwc)
re01 = arr[3].astype(np.float32)
nir01 = arr[4].astype(np.float32)
@ -148,13 +148,14 @@ def build_visual_from_saved_payload(payload_path: Path, meta: dict, cam_id: str
cv2.COLOR_GRAY2BGR
)
combined = np.vstack([
np.hstack([preview_bgr, re_bgr]),
np.hstack([nir_bgr, np.zeros_like(preview_bgr)])
])
panels = [
("RGB reconstruido", rgb_bgr, "canais 0,1,2"),
("RE reconstruido", re_bgr, "canal 3"),
("NIR reconstruido", nir_bgr, "canal 4"),
]
desc = f"Reconstruido de MULTISPEC | dtype={arr.dtype} | shape={arr.shape} | canais=[R,G,B,RE,NIR]"
return combined, desc
return panels, desc
if saved_type == "raw_native_single":
if arr.ndim == 3 and arr.shape[2] == 3 and arr.dtype == np.uint8:
@ -242,8 +243,13 @@ def build_panels_from_group(group):
panels.append(("Preview salvo", preview_saved, f"{preview_saved.shape[1]}x{preview_saved.shape[0]}"))
if group["final_raw"] is not None:
img, desc = build_visual_from_saved_payload(group["final_raw"], meta)
panels.append(("Reconstruido (final)", img, desc))
result, desc = build_visual_from_saved_payload(group["final_raw"], meta)
if isinstance(result, list):
for title, img, subtitle in result:
panels.append((title, img, subtitle))
else:
panels.append(("Reconstruido (final)", result, desc))
for cam_id, path in group["cameras"].items():
img, desc = build_visual_from_saved_payload(path, meta, cam_id=cam_id)
@ -308,7 +314,18 @@ def compose_panels(panels, max_width=1600):
def sort_panels(panels):
order = ["Preview salvo", "cam2", "cam0", "cam1"]
order = [
"preview salvo",
"rgb reconstruido",
"re reconstruido",
"nir reconstruido",
"rgb",
"re",
"nir",
"cam_a",
"cam_b",
"cam_c",
]
def key(p):
title = p[0].lower()

View File

@ -10,10 +10,6 @@ import numpy as np
from core.oak_fcc3_client import OakFcc3Client as MultiSpectralClient
# ============================================================
# Helpers gerais
# ============================================================
def now_str() -> str:
return datetime.now().strftime("%Y-%m-%d %H:%M:%S")
@ -22,14 +18,7 @@ def ensure_dir(path: str):
os.makedirs(path, exist_ok=True)
def overlay_hud(
img_bgr: np.ndarray,
lines: list[str],
x: int = 12,
y: int = 22,
font_scale: float = 0.6,
line_step: int = 24,
):
def overlay_hud(img_bgr, lines, x=12, y=22, font_scale=0.6, line_step=24):
yy = y
for s in lines:
cv2.putText(img_bgr, s, (x, yy), cv2.FONT_HERSHEY_SIMPLEX, font_scale, (0, 0, 0), 3, cv2.LINE_AA)
@ -37,30 +26,22 @@ def overlay_hud(
yy += line_step
def normalize_gray01(img: np.ndarray) -> np.ndarray:
arr = img.astype(np.float32)
mn = float(arr.min())
mx = float(arr.max())
if mx <= mn + 1e-9:
return np.zeros_like(arr, dtype=np.float32)
return (arr - mn) / (mx - mn)
def to_bgr_u8_from_rgb01(rgb01: np.ndarray) -> np.ndarray:
def to_bgr_u8_from_rgb01(rgb01):
rgb_u8 = np.clip(rgb01 * 255.0, 0, 255).astype(np.uint8)
return cv2.cvtColor(rgb_u8, cv2.COLOR_RGB2BGR)
def gray_to_color_bgr(gray01: np.ndarray, color_name: str) -> np.ndarray:
def gray_to_color_bgr(gray01, color_name):
if gray01 is None:
raise ValueError("gray01 não pode ser None")
g = np.clip(gray01 * 255.0, 0, 255).astype(np.uint8)
z = np.zeros_like(g, dtype=np.uint8)
color_name = color_name.upper()
if color_name == "RE":
# vermelho artificial
rgb = np.stack([g, z, z], axis=2)
elif color_name == "NIR":
# ciano artificial
rgb = np.stack([z, g, g], axis=2)
else:
rgb = np.stack([g, g, g], axis=2)
@ -68,33 +49,25 @@ def gray_to_color_bgr(gray01: np.ndarray, color_name: str) -> np.ndarray:
return cv2.cvtColor(rgb, cv2.COLOR_RGB2BGR)
def apply_affine(img: np.ndarray, dx: int, dy: int, theta_deg: float = 0.0) -> np.ndarray:
def apply_affine(img, dx, dy, theta_deg=0.0):
h, w = img.shape[:2]
center = (w * 0.5, h * 0.5)
M = cv2.getRotationMatrix2D(center, theta_deg, 1.0)
M[0, 2] += dx
M[1, 2] += dy
if img.ndim == 2:
return cv2.warpAffine(
img,
M,
(w, h),
flags=cv2.INTER_LINEAR,
borderMode=cv2.BORDER_CONSTANT,
borderValue=0,
)
return cv2.warpAffine(
img,
M,
(w, h),
flags=cv2.INTER_LINEAR,
borderMode=cv2.BORDER_CONSTANT,
borderValue=(0, 0, 0),
borderValue=0 if img.ndim == 2 else (0, 0, 0),
)
def apply_homography(img: np.ndarray, H) -> np.ndarray:
def apply_homography(img, H):
if H is None:
return img
@ -112,17 +85,18 @@ def apply_homography(img: np.ndarray, H) -> np.ndarray:
def build_overlay_fuse(
rgb01: np.ndarray,
spec01: np.ndarray | None,
spec_name: str,
dx: int,
dy: int,
theta_deg: float = 0.0,
alpha: float = 0.45,
calibration_mode: str = "manual_affine",
rgb01,
spec01,
spec_name,
dx,
dy,
theta_deg=0.0,
alpha=0.45,
calibration_mode="manual_affine",
H=None,
):
base_bgr = to_bgr_u8_from_rgb01(rgb01)
if spec01 is None:
return base_bgr
@ -132,47 +106,48 @@ def build_overlay_fuse(
warped = apply_affine(spec01, dx, dy, theta_deg)
spec_bgr = gray_to_color_bgr(warped, spec_name)
fused = cv2.addWeighted(base_bgr, 1.0 - alpha, spec_bgr, alpha, 0.0)
return fused
return cv2.addWeighted(base_bgr, 1.0 - alpha, spec_bgr, alpha, 0.0)
def resize_if_needed(img: np.ndarray, target_hw: tuple[int, int]) -> np.ndarray:
def resize_if_needed(img, target_hw):
if img is None:
return None
target_h, target_w = target_hw
if img.shape[:2] == (target_h, target_w):
return img
interp = cv2.INTER_LINEAR
return cv2.resize(img, (target_w, target_h), interpolation=interp)
return cv2.resize(img, (target_w, target_h), interpolation=cv2.INTER_LINEAR)
def stack_2x2(a: np.ndarray, b: np.ndarray, c: np.ndarray, d: np.ndarray) -> np.ndarray:
h = max(a.shape[0], b.shape[0], c.shape[0], d.shape[0])
w = max(a.shape[1], b.shape[1], c.shape[1], d.shape[1])
def fit(img):
if img.shape[:2] != (h, w):
return cv2.resize(img, (w, h), interpolation=cv2.INTER_NEAREST)
return img
a = fit(a)
b = fit(b)
c = fit(c)
d = fit(d)
top = np.hstack([a, b])
bottom = np.hstack([c, d])
return np.vstack([top, bottom])
def build_empty_panel_like(ref_bgr: np.ndarray, title: str) -> np.ndarray:
def build_empty_panel_like(ref_bgr, title):
img = np.zeros_like(ref_bgr)
overlay_hud(img, [title, "sem frame disponivel"], x=18, y=40, font_scale=0.8, line_step=34)
return img
def validate_module_ready(status: dict, frame_type: str, raw_policy: str, capture_mode: str):
def get_decoded_by_role(decoded, role):
role = str(role).lower()
for cam_id, item in decoded.items():
if str(item.get("role", "")).lower() == role:
return cam_id, item
return None, None
def get_image_by_role(decoded, role):
cam_id, item = get_decoded_by_role(decoded, role)
if item is None:
return cam_id, None
return cam_id, item.get("image")
def validate_module_ready(status, frame_type, raw_policy):
if not status.get("ok", True):
raise RuntimeError(f"Status inválido retornado pelo módulo: {status}")
active_ids = list(status.get("active_camera_ids", []))
active_roles = status.get("active_roles", {}) or {}
active_count = int(status.get("camera_count_active", 0))
@ -181,24 +156,19 @@ def validate_module_ready(status: dict, frame_type: str, raw_policy: str, captur
missing = [role for role in ("rgb", "nir", "re") if role not in active_roles]
if missing:
raise RuntimeError(
f"RAW_BRUTO com política require_triple exige três câmeras ativas. "
f"Faltando: {missing}. Ativas atuais: {active_ids}"
f"RAW_BRUTO com require_triple exige rgb/nir/re ativas. "
f"Faltando: {missing}. Ativas: {active_roles}"
)
else:
if active_count < 1:
raise RuntimeError("RAW_BRUTO requer ao menos uma câmera ativa, mas nenhuma foi detectada.")
elif active_count < 1:
raise RuntimeError("RAW_BRUTO requer ao menos uma câmera ativa.")
return
raise RuntimeError(f"frame_type desconhecido para validação: {frame_type}")
# ============================================================
# Persistência dos offsets
# ============================================================
def default_offsets_payload(args, effective_capture_mode: str):
def default_offsets_payload(args, effective_capture_mode):
return {
"schema": "manual_multispec_offsets_v1",
"schema": "manual_multispec_offsets_v2",
"saved_at": now_str(),
"frame_type": "RAW_BRUTO",
"capture_mode_requested": args.capture_mode,
@ -207,9 +177,9 @@ def default_offsets_payload(args, effective_capture_mode: str):
"sensor_width": args.width,
"sensor_height": args.height,
"bayer_pattern": args.bayer,
"reference_camera": "rgb",
"baseline_mm": args.baseline_mm,
"alignment_mode": "manual_affine",
"reference_camera": "rgb",
"manual_offsets": {
"re": {"dx": 0, "dy": 0, "theta_deg": 0.0},
"nir": {"dx": 0, "dy": 0, "theta_deg": 0.0},
@ -222,106 +192,61 @@ def default_offsets_payload(args, effective_capture_mode: str):
}
def load_offsets_json(path: str, args, effective_capture_mode: str):
def load_offsets_json(path, args, effective_capture_mode):
if not path or not os.path.isfile(path):
return default_offsets_payload(args, effective_capture_mode)
with open(path, "r", encoding="utf-8") as f:
data = json.load(f)
data.setdefault("schema", "manual_multispec_offsets_v1")
data.setdefault("schema", "manual_multispec_offsets_v2")
data.setdefault("reference_camera", "rgb")
data.setdefault("baseline_mm", args.baseline_mm)
data.setdefault("alignment_mode", "manual_affine")
data.setdefault("reference_camera", "rgb")
data.setdefault("manual_offsets", {})
data.setdefault("homographies", {})
data["manual_offsets"].setdefault("re", {"dx": 0, "dy": 0, "theta_deg": 0.0})
data["manual_offsets"].setdefault("nir", {"dx": 0, "dy": 0, "theta_deg": 0.0})
data["homographies"].setdefault("re_to_rgb", None)
data["homographies"].setdefault("nir_to_rgb", None)
return data
def save_offsets_json(path: str, data: dict):
def save_offsets_json(path, data):
ensure_dir(os.path.dirname(path) or ".")
data = dict(data)
data["saved_at"] = now_str()
with open(path, "w", encoding="utf-8") as f:
json.dump(data, f, ensure_ascii=False, indent=2)
def get_decoded_by_role(decoded, role):
role = str(role).lower()
for cam_id, item in decoded.items():
if str(item.get("role", "")).lower() == role:
return cam_id, item
return None, None
# ============================================================
# Main UI
# ============================================================
def main():
parser = argparse.ArgumentParser(
description="Calibrador manual de offsets para fusão RGB/RE/NIR a partir do stream RAW_BRUTO.",
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
parser.add_argument("--fps", type=int, default=20)
parser.add_argument("--width", type=int, default=640)
parser.add_argument("--height", type=int, default=480)
parser.add_argument("--bayer", default="GBRG", choices=["GBRG", "GRBG", "RGGB", "BGGR"])
parser.add_argument("--bayer", default="RGGB", choices=["GBRG", "GRBG", "RGGB", "BGGR"])
parser.add_argument("--capture_mode", default="AUTO", choices=["AUTO", "SINGLE", "DOUBLE", "TRIPLE"])
parser.add_argument("--raw_policy", default="allow_single", choices=["allow_single", "require_triple"])
parser.add_argument("--baseline_mm", type=float, default=75.0)
parser.add_argument("--preview_scale", type=float, default=1.0)
parser.add_argument("--step", type=int, default=1, help="Passo inicial em pixels ao usar as setas.")
parser.add_argument("--alpha", type=float, default=0.45, help="Alpha do overlay sobre RGB.")
parser.add_argument("--angle_step", type=float, default=0.10, help="Passo angular em graus para rotação manual.")
parser.add_argument("--step", type=int, default=1)
parser.add_argument("--alpha", type=float, default=0.45)
parser.add_argument("--angle_step", type=float, default=0.10)
parser.add_argument("--out_json", default="calibration/manual_offsets.json")
parser.add_argument("--load_json", default="", help="Se informado, carrega offsets iniciais deste arquivo.")
parser.add_argument("--load_json", default="")
parser.add_argument("--notes", default="")
args = parser.parse_args()
def on_mouse(event, x, y, flags, param):
nonlocal last_msg, last_msg_t
if event != cv2.EVENT_LBUTTONDOWN:
return
if calibration_mode != "homography":
return
if selected_cam not in ("cam0", "cam1"):
return
rgb_rect = panel_rects.get("rgb")
spec_rect = panel_rects.get(selected_cam)
def inside(rect, px, py):
if rect is None:
return False
x0, y0, x1, y1 = rect
return x0 <= px < x1 and y0 <= py < y1
def to_local(rect, px, py):
x0, y0, x1, y1 = rect
return float(px - x0), float(py - y0)
if inside(spec_rect, x, y):
pt = to_local(spec_rect, x, y)
#if len(selected_points_spec[selected_cam]) < 4:
selected_points_spec[selected_cam].append(pt)
last_msg = f"{selected_cam}: ponto SPEC #{len(selected_points_spec[selected_cam])}"
last_msg_t = time.time()
return
if inside(rgb_rect, x, y):
pt = to_local(rgb_rect, x, y)
#if len(selected_points_rgb[selected_cam]) < 4:
selected_points_rgb[selected_cam].append(pt)
last_msg = f"{selected_cam}: ponto RGB #{len(selected_points_rgb[selected_cam])}"
last_msg_t = time.time()
return
effective_capture_mode = args.capture_mode
offsets_data = load_offsets_json(args.load_json, args, effective_capture_mode)
@ -330,23 +255,21 @@ def main():
selected_role = "re"
calibration_mode = offsets_data.get("alignment_mode", "manual_affine")
selected_points_spec = {
"re": [],
"nir": [],
}
selected_points_rgb = {
"re": [],
"nir": [],
}
selected_points_spec = {"re": [], "nir": []}
selected_points_rgb = {"re": [], "nir": []}
panel_rects = {
"fuse": None,
"rgb": None,
"re": None,
"nir": None,
}
decoded_last = {}
last_msg = ""
last_msg_t = 0.0
last_frame_id = -1
fps_view = 0.0
fps_stream = 0.0
t_view_fps = time.time()
@ -355,8 +278,57 @@ def main():
stream_frames_accum = 0
last_stream_frame_id = None
decoded_last = {}
window_name = "Manual Fusion Calibrator"
def inside(rect, px, py):
if rect is None:
return False
x0, y0, x1, y1 = rect
return x0 <= px < x1 and y0 <= py < y1
def to_local(rect, px, py):
x0, y0, _, _ = rect
return float(px - x0), float(py - y0)
def on_mouse(event, x, y, flags, param):
nonlocal last_msg, last_msg_t, selected_role, calibration_mode
if event != cv2.EVENT_LBUTTONDOWN:
return
if calibration_mode != "homography":
return
if selected_role not in ("re", "nir"):
return
rgb_rect = panel_rects.get("rgb")
spec_rect = panel_rects.get(selected_role)
if inside(spec_rect, x, y):
pt = to_local(spec_rect, x, y)
selected_points_spec[selected_role].append(pt)
last_msg = f"{selected_role.upper()}: ponto SPEC #{len(selected_points_spec[selected_role])}"
last_msg_t = time.time()
return
if inside(rgb_rect, x, y):
pt = to_local(rgb_rect, x, y)
selected_points_rgb[selected_role].append(pt)
last_msg = f"{selected_role.upper()}: ponto RGB #{len(selected_points_rgb[selected_role])}"
last_msg_t = time.time()
return
def get_preview_panel_by_role(previews, meta, role):
camera_info = meta.get("camera_info", {}) or {}
for cam_id, preview in previews.items():
info = camera_info.get(cam_id, {}) or {}
if str(info.get("role", "")).lower() == role:
return preview
return None
cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
cv2.setMouseCallback(window_name, on_mouse)
@ -366,17 +338,22 @@ def main():
height=args.height,
bayer=args.bayer,
fps=args.fps,
frame_type="RAW_BRUTO",
frame_type="PREVIEW",
output_dtype="uint8",
capture_mode=effective_capture_mode,
raw_policy=args.raw_policy,
module_calibration_json=None,
radiometric_enabled=True
module_calibration_json="calibration/module_params.json",
radiometric_enabled=False,
) as cam:
validate_module_ready(cam.get_status(), "RAW_BRUTO", args.raw_policy)
previews_last = {}
while True:
t0 = time.time()
frame, meta, decoded = cam.get_next_decoded(timeout=2.0)
previews_last = cam.build_visual_preview_from_raw(frame, meta)
if meta is not None and frame is not None and meta.get("frame_id") != last_frame_id:
last_frame_id = meta["frame_id"]
@ -405,40 +382,46 @@ def main():
t_view_fps = time.time()
if decoded_last:
rgb_id, rgb_item = get_decoded_by_role(decoded_last, "rgb")
re_id, re_item = get_decoded_by_role(decoded_last, "re")
nir_id, nir_item = get_decoded_by_role(decoded_last, "nir")
rgb01 = rgb_item.get("image") if rgb_item else None
re01 = re_item.get("image") if re_item else None
nir01 = nir_item.get("image") if nir_item else None
rgb_id, rgb01 = get_image_by_role(decoded_last, "rgb")
re_id, re01 = get_image_by_role(decoded_last, "re")
nir_id, nir01 = get_image_by_role(decoded_last, "nir")
if rgb01 is None:
# fallback para exibição quando não houver RGB
if re01 is not None:
rgb01 = np.stack([re01, re01, re01], axis=2)
rgb_id = "fallback_re"
elif nir01 is not None:
rgb01 = np.stack([nir01, nir01, nir01], axis=2)
rgb_id = "fallback_nir"
else:
rgb01 = np.zeros((args.height, args.width, 3), dtype=np.float32)
rgb_id = "empty"
base_h, base_w = rgb01.shape[:2]
if re01 is not None:
re01 = resize_if_needed(re01, (base_h, base_w))
if nir01 is not None:
nir01 = resize_if_needed(nir01, (base_h, base_w))
re01 = resize_if_needed(re01, (base_h, base_w))
nir01 = resize_if_needed(nir01, (base_h, base_w))
rgb_panel = to_bgr_u8_from_rgb01(rgb01)
re_panel = gray_to_color_bgr(re01, "RE") if re01 is not None else build_empty_panel_like(rgb_panel, "RE")
nir_panel = gray_to_color_bgr(nir01, "NIR") if nir01 is not None else build_empty_panel_like(rgb_panel, "NIR")
rgb_panel = get_preview_panel_by_role(previews_last, meta, "rgb")
re_panel = get_preview_panel_by_role(previews_last, meta, "re")
nir_panel = get_preview_panel_by_role(previews_last, meta, "nir")
if rgb_panel is None:
rgb_panel = to_bgr_u8_from_rgb01(rgb01)
if re_panel is None:
re_panel = gray_to_color_bgr(re01, "RE") if re01 is not None else build_empty_panel_like(rgb_panel, "RE")
if nir_panel is None:
nir_panel = gray_to_color_bgr(nir01, "NIR") if nir01 is not None else build_empty_panel_like(rgb_panel, "NIR")
active_spec_name = selected_role.upper()
active_spec = re01 if selected_role == "re" else nir01
active_spec_name = "RE" if selected_role == "cam0" else "NIR"
active_spec = re01 if selected_role == "cam0" else nir01
dx = int(offsets.get(selected_role, {}).get("dx", 0))
dy = int(offsets.get(selected_role, {}).get("dy", 0))
theta_deg = float(offsets.get(selected_role, {}).get("theta_deg", 0.0))
H_key = f"{selected_role}_to_cam2"
H_key = f"{selected_role}_to_rgb"
H = offsets_data.get("homographies", {}).get(H_key)
fuse_panel = build_overlay_fuse(
@ -453,28 +436,37 @@ def main():
H=H,
)
spec_pts = len(selected_points_spec[selected_cam])
rgb_pts = len(selected_points_rgb[selected_cam])
spec_pts = len(selected_points_spec[selected_role])
rgb_pts = len(selected_points_rgb[selected_role])
lines_fuse = [
f"FUSE: RGB + {active_spec_name}",
f"mode={calibration_mode} | selecionada={selected_cam}",
f"mode={calibration_mode} | selecionada={selected_role.upper()}",
f"dx={dx} | dy={dy} | theta={theta_deg:.2f}g | step={args.step} | ang_step={args.angle_step:.2f}g",
f"pts_spec={spec_pts} | pts_rgb={rgb_pts} | min=4 | fps_stream={fps_stream:.1f} | fps_view={fps_view:.1f}"
f"pts_spec={spec_pts} | pts_rgb={rgb_pts} | min=4 | fps_stream={fps_stream:.1f} | fps_view={fps_view:.1f}",
]
overlay_hud(fuse_panel, lines_fuse)
lines_rgb = ["RGB (cam2)"]
overlay_hud(rgb_panel, lines_rgb)
overlay_hud(rgb_panel, [f"RGB ({rgb_id})"], y=24)
re_dx = int(offsets.get("cam0", {}).get("dx", 0))
re_dy = int(offsets.get("cam0", {}).get("dy", 0))
re_theta = float(offsets.get("cam0", {}).get("theta_deg", 0.0))
nir_dx = int(offsets.get("cam1", {}).get("dx", 0))
nir_dy = int(offsets.get("cam1", {}).get("dy", 0))
nir_theta = float(offsets.get("cam1", {}).get("theta_deg", 0.0))
overlay_hud(re_panel, [f"RE (cam0) | dx={re_dx} dy={re_dy} th={re_theta:.2f}g", "2 seleciona RE"], y=24)
overlay_hud(nir_panel, [f"NIR (cam1) | dx={nir_dx} dy={nir_dy} th={nir_theta:.2f}g", "3 seleciona NIR"], y=24)
re_dx = int(offsets.get("re", {}).get("dx", 0))
re_dy = int(offsets.get("re", {}).get("dy", 0))
re_theta = float(offsets.get("re", {}).get("theta_deg", 0.0))
nir_dx = int(offsets.get("nir", {}).get("dx", 0))
nir_dy = int(offsets.get("nir", {}).get("dy", 0))
nir_theta = float(offsets.get("nir", {}).get("theta_deg", 0.0))
overlay_hud(
re_panel,
[f"RE ({re_id}) | dx={re_dx} dy={re_dy} th={re_theta:.2f}g", "2 seleciona RE"],
y=24,
)
overlay_hud(
nir_panel,
[f"NIR ({nir_id}) | dx={nir_dx} dy={nir_dy} th={nir_theta:.2f}g", "3 seleciona NIR"],
y=24,
)
ph = max(fuse_panel.shape[0], rgb_panel.shape[0], re_panel.shape[0], nir_panel.shape[0])
pw = max(fuse_panel.shape[1], rgb_panel.shape[1], re_panel.shape[1], nir_panel.shape[1])
@ -491,21 +483,52 @@ def main():
panel_rects["fuse"] = (0, 0, pw, ph)
panel_rects["rgb"] = (pw, 0, pw * 2, ph)
panel_rects["cam0"] = (0, ph, pw, ph * 2)
panel_rects["cam1"] = (pw, ph, pw * 2, ph * 2)
panel_rects["re"] = (0, ph, pw, ph * 2)
panel_rects["nir"] = (pw, ph, pw * 2, ph * 2)
top = np.hstack([fuse_panel, rgb_panel])
bottom = np.hstack([re_panel, nir_panel])
board = np.vstack([top, bottom])
help_lines = [
"M=manual_affine | H=homography | clique pares correspondentes | >=4 pares | SPACE=salva | C=limpa pts | Z=zera sel | X=zera tudo",
"A/W/S/D movem | J/L rotacionam | O/P muda passo angular | I/U remove ultimo ponto | ENTER calcula H | TAB alterna camera | Q/Esc sai",
"M=manual_affine | H=homography | clique pares | >=4 pares | SPACE=salva | C=limpa pts | Z=zera sel | X=zera tudo",
"A/W/S/D movem | J/L rotacionam | O/P ang_step | I/U remove ponto | ENTER calcula H | TAB alterna RE/NIR | Q/Esc sai",
]
overlay_hud(board, help_lines, x=16, y=board.shape[0] - 44, font_scale=0.55, line_step=20)
if last_msg and (time.time() - last_msg_t) < 2.5:
cv2.putText(board, last_msg, (16, board.shape[0] - 72), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2, cv2.LINE_AA)
cv2.putText(
board,
last_msg,
(16, board.shape[0] - 72),
cv2.FONT_HERSHEY_SIMPLEX,
0.7,
(0, 255, 0),
2,
cv2.LINE_AA,
)
if calibration_mode == "homography":
color_spec = (0, 255, 255)
color_rgb = (0, 255, 0)
for idx, pt in enumerate(selected_points_spec[selected_role]):
rect = panel_rects[selected_role]
if rect is not None:
x0, y0, _, _ = rect
px = int(x0 + pt[0])
py = int(y0 + pt[1])
cv2.circle(board, (px, py), 5, color_spec, -1)
cv2.putText(board, str(idx + 1), (px + 6, py - 6), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color_spec, 1, cv2.LINE_AA)
for idx, pt in enumerate(selected_points_rgb[selected_role]):
rect = panel_rects["rgb"]
if rect is not None:
x0, y0, _, _ = rect
px = int(x0 + pt[0])
py = int(y0 + pt[1])
cv2.circle(board, (px, py), 5, color_rgb, -1)
cv2.putText(board, str(idx + 1), (px + 6, py - 6), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color_rgb, 1, cv2.LINE_AA)
if args.preview_scale != 1.0:
board = cv2.resize(
@ -514,57 +537,39 @@ def main():
interpolation=cv2.INTER_NEAREST,
)
if calibration_mode == "homography":
color_spec = (0, 255, 255)
color_rgb = (0, 255, 0)
for idx, pt in enumerate(selected_points_spec[selected_cam]):
rect = panel_rects[selected_cam]
if rect is not None:
x0, y0, _, _ = rect
px = int(x0 + pt[0])
py = int(y0 + pt[1])
cv2.circle(board, (px, py), 5, color_spec, -1)
cv2.putText(board, str(idx + 1), (px + 6, py - 6),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, color_spec, 1, cv2.LINE_AA)
for idx, pt in enumerate(selected_points_rgb[selected_cam]):
rect = panel_rects["rgb"]
if rect is not None:
x0, y0, _, _ = rect
px = int(x0 + pt[0])
py = int(y0 + pt[1])
cv2.circle(board, (px, py), 5, color_rgb, -1)
cv2.putText(board, str(idx + 1), (px + 6, py - 6),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, color_rgb, 1, cv2.LINE_AA)
cv2.imshow(window_name, board)
else:
blank = np.zeros((720, 1280, 3), dtype=np.uint8)
overlay_hud(blank, ["Aguardando frames do módulo..."], x=40, y=80, font_scale=1.0, line_step=34)
cv2.imshow(window_name, blank)
k = cv2.waitKey(1) & 0xFF
if k in (ord("q"), ord("Q"), 27):
break
elif k in (ord("m"), ord("M")):
calibration_mode = "manual_affine"
offsets_data["alignment_mode"] = calibration_mode
last_msg = "Modo: manual_affine"
last_msg_t = time.time()
elif k in (ord("h"), ord("H")):
calibration_mode = "homography"
offsets_data["alignment_mode"] = calibration_mode
last_msg = "Modo: homography"
last_msg_t = time.time()
elif k in (ord("c"), ord("C")):
selected_points_spec[selected_cam] = []
selected_points_rgb[selected_cam] = []
last_msg = f"Pontos limpos: {selected_cam}"
selected_points_spec[selected_role] = []
selected_points_rgb[selected_role] = []
last_msg = f"Pontos limpos: {selected_role.upper()}"
last_msg_t = time.time()
elif k == 13: # ENTER
spec_pts = selected_points_spec[selected_cam]
rgb_pts = selected_points_rgb[selected_cam]
elif k == 13:
spec_pts = selected_points_spec[selected_role]
rgb_pts = selected_points_rgb[selected_role]
if len(spec_pts) >= 4 and len(rgb_pts) >= 4 and len(spec_pts) == len(rgb_pts):
src = np.array(spec_pts, dtype=np.float32)
@ -573,109 +578,131 @@ def main():
H, status = cv2.findHomography(src, dst, method=cv2.RANSAC)
if H is not None:
offsets_data.setdefault("homographies", {})
offsets_data["homographies"][f"{selected_cam}_to_cam2"] = H.tolist()
offsets_data["homographies"][f"{selected_role}_to_rgb"] = H.tolist()
inliers = int(status.sum()) if status is not None else len(spec_pts)
last_msg = f"H calculada para {selected_cam} | pts={len(spec_pts)} | inliers={inliers}"
last_msg = f"H calculada para {selected_role.upper()} | pts={len(spec_pts)} | inliers={inliers}"
else:
last_msg = f"Falha ao calcular H para {selected_cam}"
last_msg = f"Falha ao calcular H para {selected_role.upper()}"
else:
last_msg = f"{selected_cam}: precisa de >=4 pares e mesmo numero de pontos"
last_msg = f"{selected_role.upper()}: precisa de >=4 pares e mesmo numero de pontos"
last_msg_t = time.time()
elif k == ord("2"):
if "cam0" in decoded_last:
selected_cam = "cam0"
last_msg = "Selecionada: cam0 / RE"
_, item = get_decoded_by_role(decoded_last, "re")
if item is not None:
selected_role = "re"
last_msg = "Selecionada: RE"
else:
last_msg = "cam0 / RE nao disponivel neste frame"
last_msg = "RE nao disponivel neste frame"
last_msg_t = time.time()
elif k == ord("3"):
if "cam1" in decoded_last:
selected_cam = "cam1"
last_msg = "Selecionada: cam1 / NIR"
_, item = get_decoded_by_role(decoded_last, "nir")
if item is not None:
selected_role = "nir"
last_msg = "Selecionada: NIR"
else:
last_msg = "cam1 / NIR nao disponivel neste frame"
last_msg = "NIR nao disponivel neste frame"
last_msg_t = time.time()
elif k == 9: # TAB
choices = [cid for cid in ("cam0", "cam1") if cid in decoded_last]
elif k == 9:
choices = [role for role in ("re", "nir") if get_decoded_by_role(decoded_last, role)[1] is not None]
if len(choices) >= 2:
selected_cam = choices[1] if selected_cam == choices[0] else choices[0]
last_msg = f"Selecionada: {selected_cam}"
selected_role = choices[1] if selected_role == choices[0] else choices[0]
last_msg = f"Selecionada: {selected_role.upper()}"
last_msg_t = time.time()
elif k in (ord("z"), ord("Z")):
offsets.setdefault(selected_cam, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_cam]["dx"] = 0
offsets[selected_cam]["dy"] = 0
offsets[selected_cam]["theta_deg"] = 0.0
last_msg = f"Offset zerado: {selected_cam}"
offsets.setdefault(selected_role, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_role] = {"dx": 0, "dy": 0, "theta_deg": 0.0}
last_msg = f"Offset zerado: {selected_role.upper()}"
last_msg_t = time.time()
elif k in (ord("x"), ord("X")):
offsets["cam0"] = {"dx": 0, "dy": 0, "theta_deg": 0.0}
offsets["cam1"] = {"dx": 0, "dy": 0, "theta_deg": 0.0}
offsets["re"] = {"dx": 0, "dy": 0, "theta_deg": 0.0}
offsets["nir"] = {"dx": 0, "dy": 0, "theta_deg": 0.0}
last_msg = "Todos offsets zerados"
last_msg_t = time.time()
elif k == 32:
# Se uma câmera não apareceu, salva zerada como pedido
if "cam0" not in decoded_last:
offsets["cam0"] = {"dx": 0, "dy": 0, "theta_deg": 0.0}
if "cam1" not in decoded_last:
offsets["cam1"] = {"dx": 0, "dy": 0, "theta_deg": 0.0}
if get_decoded_by_role(decoded_last, "re")[1] is None:
offsets["re"] = {"dx": 0, "dy": 0, "theta_deg": 0.0}
if get_decoded_by_role(decoded_last, "nir")[1] is None:
offsets["nir"] = {"dx": 0, "dy": 0, "theta_deg": 0.0}
offsets_data["manual_offsets"] = offsets
offsets_data.setdefault("homographies", {})
offsets_data["schema"] = "manual_multispec_offsets_v2"
offsets_data["reference_camera"] = "rgb"
save_offsets_json(args.out_json, offsets_data)
last_msg = f"Offsets salvos em: {args.out_json}"
last_msg_t = time.time()
elif k in (ord("+"), ord("=")):
args.step = min(args.step + 1, 50)
last_msg = f"Step -> {args.step}px"
last_msg_t = time.time()
elif k in (ord("-"), ord("_")):
args.step = max(args.step - 1, 1)
last_msg = f"Step -> {args.step}px"
last_msg_t = time.time()
elif k in (ord("a"), ord("A")):
if selected_cam in decoded_last:
offsets.setdefault(selected_cam, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_cam]["dx"] -= args.step
if get_decoded_by_role(decoded_last, selected_role)[1] is not None:
offsets.setdefault(selected_role, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_role]["dx"] -= args.step
elif k in (ord("d"), ord("D")):
if selected_cam in decoded_last:
offsets.setdefault(selected_cam, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_cam]["dx"] += args.step
if get_decoded_by_role(decoded_last, selected_role)[1] is not None:
offsets.setdefault(selected_role, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_role]["dx"] += args.step
elif k in (ord("w"), ord("W")):
if selected_cam in decoded_last:
offsets.setdefault(selected_cam, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_cam]["dy"] -= args.step
if get_decoded_by_role(decoded_last, selected_role)[1] is not None:
offsets.setdefault(selected_role, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_role]["dy"] -= args.step
elif k in (ord("s"), ord("S")):
if selected_cam in decoded_last:
offsets.setdefault(selected_cam, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_cam]["dy"] += args.step
if get_decoded_by_role(decoded_last, selected_role)[1] is not None:
offsets.setdefault(selected_role, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_role]["dy"] += args.step
elif k in (ord("j"), ord("J")):
if selected_cam in decoded_last:
offsets.setdefault(selected_cam, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_cam]["theta_deg"] -= args.angle_step
if get_decoded_by_role(decoded_last, selected_role)[1] is not None:
offsets.setdefault(selected_role, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_role]["theta_deg"] -= args.angle_step
elif k in (ord("l"), ord("L")):
if selected_cam in decoded_last:
offsets.setdefault(selected_cam, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_cam]["theta_deg"] += args.angle_step
if get_decoded_by_role(decoded_last, selected_role)[1] is not None:
offsets.setdefault(selected_role, {"dx": 0, "dy": 0, "theta_deg": 0.0})
offsets[selected_role]["theta_deg"] += args.angle_step
elif k in (ord("o"), ord("O")):
args.angle_step = max(args.angle_step - 0.05, 0.01)
last_msg = f"Angle step -> {args.angle_step:.2f}°"
last_msg_t = time.time()
elif k in (ord("p"), ord("P")):
args.angle_step = min(args.angle_step + 0.05, 5.0)
last_msg = f"Angle step -> {args.angle_step:.2f}°"
last_msg_t = time.time()
elif k in (ord("u"), ord("U")):
if selected_points_spec[selected_cam]:
selected_points_spec[selected_cam].pop()
last_msg = f"Removido ultimo ponto SPEC de {selected_cam}"
if selected_points_spec[selected_role]:
selected_points_spec[selected_role].pop()
last_msg = f"Removido ultimo ponto SPEC de {selected_role.upper()}"
last_msg_t = time.time()
elif k in (ord("i"), ord("I")):
if selected_points_rgb[selected_cam]:
selected_points_rgb[selected_cam].pop()
last_msg = f"Removido ultimo ponto RGB de {selected_cam}"
if selected_points_rgb[selected_role]:
selected_points_rgb[selected_role].pop()
last_msg = f"Removido ultimo ponto RGB de {selected_role.upper()}"
last_msg_t = time.time()
dt_loop = time.time() - t0
if dt_loop < 0.001:
time.sleep(0.001)
@ -686,4 +713,4 @@ def main():
if __name__ == "__main__":
main()
main()