113 lines
3.6 KiB
Python
113 lines
3.6 KiB
Python
from collections import deque
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import json
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import os
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import time
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import cv2
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import numpy as np
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import torch
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from gal5000.gal_service import Gal5000Camera
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from raw_segformer_service import RawSegformerService
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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print(f"Device: {device}")
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INFERIR = False
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cfg_path = r"config.json"
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# ---- Carrega config ----
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with open(cfg_path, "r") as f:
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config = json.load(f)
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MODELO = config["camera"] # ex: "gal5000"
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MODEL_NAME = config["model_name"] # ex: "segformer_b3"
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modelo_folder = config["modelo"] # ex: "dif"
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USE_NDVI = bool(config.get("use_ndvi", False))
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CHANNELS = int(config.get("channels", 4))
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RESOLUCAO = config["resolucao"]
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W, H = RESOLUCAO[0], RESOLUCAO[1]
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preview_w = RESOLUCAO[0]
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preview_h = RESOLUCAO[1]
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fps_window = 30
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if INFERIR:
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save_path = os.path.join(MODELO, "backup", modelo_folder, MODEL_NAME, f"raw{CHANNELS}")
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ckpt_path = os.path.join(save_path, "best_miou.pt")
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# ---- Instancia service do modelo RAW (4 ou 5 canais) ----
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model_svc = RawSegformerService(
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config_path=cfg_path,
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ckpt_path=ckpt_path,
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device=device,
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use_amp=True,
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)
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print("[mode] Câmera ao vivo (GAL5000 + SegFormer RAW)")
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cam = Gal5000Camera(raw_w=W, raw_h=H, use_auto_exposure=True)
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win = "GAL5000 RAW + SegFormer (Q=quit)"
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cv2.namedWindow(win, cv2.WINDOW_NORMAL)
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tq = deque(maxlen=max(5, int(fps_window)))
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with cam:
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#cam.configure_scaling_and_fps(bin_h=2, bin_v=2, dec_h=1, dec_v=1, fps=20.0)
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cam.configure_fps(fps_window)
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cam.start_streaming()
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while True:
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t0 = time.time()
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# raw4_base: (4,H,W) float32 0..1 [R,G,IR,B] já redimensionado
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raw4_base, dbg = cam.grab_raw4(out_h=preview_h, out_w=preview_w, timeout_ms=2000)
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# Separa canais básicos
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r = raw4_base[0]
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g = raw4_base[1]
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ir = raw4_base[2]
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b = raw4_base[3]
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if INFERIR:
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# Deixa o service montar a entrada final com 4 ou 5 canais
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# (R,G,IR,B) | (R,G,B,NDVI) | (R,G,B,IR,NDVI)
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raw_input = model_svc.build_raw_input(r, g, ir, b) # (C,H,W) float32 0..1
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# Inferência + previews via service
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pred_ids, rgb, pred_rgb, overlay, t_inf, t_pvw = model_svc.infer_and_preview(raw_input)
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else:
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rgb = np.stack([r, g, b], axis=0) # (3,H,W)
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rgb = (rgb * 255.0).clip(0, 255).astype("uint8")
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overlay = np.transpose(rgb, (1, 2, 0)) # (H,W,3) -> formato OpenCV
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overlay = np.ascontiguousarray(overlay)
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if overlay.dtype != np.uint8:
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overlay = overlay.astype(np.uint8)
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tq.append(time.time() - t0)
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fps = 1.0 / (sum(tq) / len(tq))
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status = cam.get_status()
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shape = dbg["raw_shape"]
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lat = dbg["latency_s"] * 1000
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tc = dbg.get("t_capture", 0) * 1000
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tconv = dbg.get("t_convert", 0) * 1000
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t_ae = dbg.get("t_ae", 0) * 1000
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lines = [
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f"{preview_w}x{preview_h} | FPS~{fps:.1f} | {shape}",
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f"EX={status['exp_raw']} G={status['gain_a']}/{status['gain_d']}",
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f"C={CHANNELS} NDVI={int(USE_NDVI)}",
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f"cap={tc:.1f}ms ae={t_ae:.1f}ms conv={tconv:.1f}ms",
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]
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y = 24
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for line in lines:
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cv2.putText(overlay, line, (12, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 1, cv2.LINE_AA)
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y += 22
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cv2.imshow(win, cv2.cvtColor(overlay, cv2.COLOR_RGB2BGR))
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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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cv2.destroyAllWindows() |