142 lines
3.2 KiB
Python
142 lines
3.2 KiB
Python
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import cv2
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import numpy as np
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import os
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from ultralytics import YOLO
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# ---------------- 配置 ----------------
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MODEL_PATH = "/home/hx/yolo/ultralytics_yolo11-main/runs/train/61seg/exp/weights/best.pt"
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IMAGE_PATH = "2.png"
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OUT_DIR = "outputs"
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IMG_SIZE = 640
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CONF_THRES = 0.25
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ALPHA = 0.5
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# -------------------------------------
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def get_color(idx):
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np.random.seed(idx)
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return tuple(int(x) for x in np.random.randint(0, 255, 3))
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def draw_segmentation(frame, result):
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"""
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原样保留你的可视化逻辑
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"""
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overlay = frame.copy()
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if result.masks is None:
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return frame
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boxes = result.boxes
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names = result.names
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for i, poly in enumerate(result.masks.xy):
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cls_id = int(boxes.cls[i])
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conf = float(boxes.conf[i])
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if conf < CONF_THRES:
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continue
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color = get_color(cls_id)
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poly = poly.astype(np.int32)
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# 填充 mask
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cv2.fillPoly(overlay, [poly], color)
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# 轮廓
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cv2.polylines(overlay, [poly], True, color, 2)
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# 标签
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x, y = poly[0]
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label = f"{names[cls_id]} {conf:.2f}"
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cv2.putText(
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overlay,
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label,
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(x, max(y - 5, 20)),
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cv2.FONT_HERSHEY_SIMPLEX,
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0.6,
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color,
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2
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)
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return cv2.addWeighted(overlay, ALPHA, frame, 1 - ALPHA, 0)
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def save_masks_as_yolo_seg(result, img_shape, save_path):
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"""
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保存 YOLO segmentation 标注（txt）
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格式：
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class_id x1 y1 x2 y2 ...（全部归一化）
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"""
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if result.masks is None:
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return
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h, w = img_shape[:2]
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boxes = result.boxes
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lines = []
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for i, poly in enumerate(result.masks.xy):
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cls_id = int(boxes.cls[i])
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conf = float(boxes.conf[i])
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if conf < CONF_THRES:
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continue
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poly_norm = []
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for x, y in poly:
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poly_norm.append(f"{x / w:.6f}")
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poly_norm.append(f"{y / h:.6f}")
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line = str(cls_id) + " " + " ".join(poly_norm)
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lines.append(line)
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if lines:
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with open(save_path, "w") as f:
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f.write("\n".join(lines))
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def run_image_inference():
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os.makedirs(OUT_DIR, exist_ok=True)
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# 加载模型
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model = YOLO(MODEL_PATH)
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# 读取图片
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img = cv2.imread(IMAGE_PATH)
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if img is None:
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raise FileNotFoundError(f"❌ 无法读取图片: {IMAGE_PATH}")
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# 推理
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results = model(
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img,
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imgsz=IMG_SIZE,
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conf=CONF_THRES,
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verbose=False
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)
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result = results[0]
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# 1️⃣ 保存可视化结果
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vis = draw_segmentation(img, result)
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out_img_path = os.path.join(
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OUT_DIR,
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os.path.splitext(os.path.basename(IMAGE_PATH))[0] + "_seg.png"
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)
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cv2.imwrite(out_img_path, vis)
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# 2️⃣ 保存 YOLO segmentation 标注
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out_txt_path = os.path.join(
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OUT_DIR,
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os.path.splitext(os.path.basename(IMAGE_PATH))[0] + ".txt"
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)
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save_masks_as_yolo_seg(result, img.shape, out_txt_path)
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print("✅ 推理完成")
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print(f"🖼 可视化结果: {out_img_path}")
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print(f"📄 YOLO Seg 标注: {out_txt_path}")
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if __name__ == "__main__":
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run_image_inference()
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