97 lines
2.3 KiB
Python
97 lines
2.3 KiB
Python
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 = "seg.pt"
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IMAGE_PATH = "1.png" # 支持任意路径
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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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仅填充 mask（无标签、无轮廓、无线段）
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返回每个 mask 的类别名和水平宽度（max_x - min_x）
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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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widths = []
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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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# 计算水平宽度：最右 x - 最左 x
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min_x = np.min(poly[:, 0])
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max_x = np.max(poly[:, 0])
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width = max_x - min_x
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widths.append((result.names[cls_id], width))
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# 仅填充 mask（无其他绘制）
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cv2.fillPoly(overlay, [poly], color)
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blended = cv2.addWeighted(overlay, ALPHA, frame, 1 - ALPHA, 0)
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return blended, widths
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def run_image_inference():
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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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print(f"📷 正在处理: {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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# 生成可视化图（仅 mask 填充）
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vis, widths = draw_segmentation(img, result)
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# 保存到原图所在目录
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base_name = os.path.splitext(IMAGE_PATH)[0]
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out_path = base_name + "_seg.png"
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cv2.imwrite(out_path, vis)
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# 打印宽度信息（仅文本，不画图）
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print("\nMask 水平宽度 (像素):")
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if widths:
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for name, width in widths:
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print(f" • {name}: {width:.1f}")
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else:
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print(" (无有效 mask)")
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print(f"\n完成！结果已保存至:\n {out_path}")
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if __name__ == "__main__":
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run_image_inference() |