109 lines
3.2 KiB
Python
109 lines
3.2 KiB
Python
from ultralytics import YOLO
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import cv2
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import numpy as np
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import os
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import torch
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import torch.nn.functional as F
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# ------------------ 模型与路径配置 ------------------
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MODEL_PATH = 'ultralytics_yolo11-main/runs/train/exp4/weights/best.pt'
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OUTPUT_DIR = 'test_image'
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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model = YOLO(MODEL_PATH)
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model.to('cuda')
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def detect_jaw_angle_fast(image_path, mode='silent'):
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img = cv2.imread(image_path)
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if img is None:
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raise FileNotFoundError(f"无法读取图像: {image_path}")
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h, w = img.shape[:2]
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filename = os.path.basename(image_path)
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name_only = os.path.splitext(filename)[0]
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# 推理（批量可进一步提速）
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results = model(image_path, imgsz=1280, conf=0.5, device='cuda')
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r = results[0]
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if r.masks is None:
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return None
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# 【优化1】一次性上采样所有 masks
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masks_tensor = r.masks.data # [N, h_m, w_m]
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boxes = r.boxes.xyxy.cpu().numpy()
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masks = F.interpolate(
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masks_tensor.unsqueeze(0).float(),
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size=(h, w),
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mode='bilinear',
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align_corners=False
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)
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masks = (masks[0] > 0.5).cpu().numpy().astype(np.uint8) # [N, h, w]
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jaws = []
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for i, (mask, box) in enumerate(zip(masks, boxes)):
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x1, y1, x2, y2 = map(int, box)
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# 【优化4】提前过滤小框
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if (x2 - x1) * (y2 - y1) < 100:
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continue
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# 【优化2】裁剪区域
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x1c, y1c = max(0, x1), max(0, y1)
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x2c, y2c = min(w, x2), min(h, y2)
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mask_crop = mask[y1c:y2c, x1c:x2c]
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# 【优化3】使用 findNonZero + convexHull
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coords = cv2.findNonZero(mask_crop)
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if coords is None or len(coords) < 5:
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continue
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hull = cv2.convexHull(coords)
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area = cv2.contourArea(hull)
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if area < 100:
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continue
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rect = cv2.minAreaRect(hull)
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jaws.append({'rect': rect, 'area': area})
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if len(jaws) < 2:
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return None
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jaws = sorted(jaws, key=lambda x: x['area'], reverse=True)[:2]
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rect1, rect2 = jaws[0]['rect'], jaws[1]['rect']
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def get_angle(rect):
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w, h = rect[1]
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angle = rect[2]
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return angle + 90 if w < h else angle
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angle1 = get_angle(rect1) % 180
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angle2 = get_angle(rect2) % 180
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opening_angle = min(abs(angle1 - angle2), 180 - abs(angle1 - angle2))
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# 可视化（可选）
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if mode == 'show':
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vis = np.zeros((h, w, 3), dtype=np.uint8)
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box1 = cv2.boxPoints(rect1)
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box2 = cv2.boxPoints(rect2)
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cv2.drawContours(vis, [np.int32(box1)], 0, (0, 0, 255), 2)
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cv2.drawContours(vis, [np.int32(box2)], 0, (255, 0, 0), 2)
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cv2.putText(vis, f"{opening_angle:.1f}°", (20, 50),
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cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 255, 0), 2)
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cv2.imwrite(os.path.join(OUTPUT_DIR, f"fast_{name_only}.png"), vis)
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return round(opening_angle, 2)
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# ------------------ 测试 ------------------
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if __name__ == '__main__':
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image_path = '/home/hx/yolo/test_image/1.png'
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print(f"🚀 处理: {image_path}")
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angle = detect_jaw_angle_fast(image_path, mode='silent')
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if angle is not None:
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print(f"✅ 角度: {angle}°")
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else:
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print("❌ 未检测到两个夹具") |