Add YOLO11 TensorRT quantization benchmark scripts

- Engine build scripts (FP16/INT8) - Benchmark validation scripts - Result parsing and analysis tools - COCO dataset configuration
2026-01-29 13:59:42 +08:00
commit 942244bd88
34 changed files with 3514 additions and 0 deletions
--- a/generate_coco_labels.py
+++ b/generate_coco_labels.py
@@ -0,0 +1,69 @@
+import json
+from pathlib import Path
+from pycocotools.coco import COCO
+
+def generate_coco_labels(annotations_file, images_dir, labels_dir):
+    """从COCO JSON标注生成YOLO格式标签"""
+    annotations_file = Path(annotations_file)
+    images_dir = Path(images_dir)
+    labels_dir = Path(labels_dir)
+    
+    labels_dir.mkdir(parents=True, exist_ok=True)
+    
+    print(f"Loading annotations from {annotations_file}...")
+    coco = COCO(str(annotations_file))
+    
+    img_ids = sorted(coco.getImgIds())
+    
+    total_boxes = 0
+    
+    for img_id in img_ids:
+        img_info = coco.loadImgs(img_id)[0]
+        img_name = img_info['file_name']
+        img_path = images_dir / img_name
+        
+        if not img_path.exists():
+            continue
+        
+        ann_ids = coco.getAnnIds(imgIds=img_id)
+        anns = coco.loadAnns(ann_ids)
+        
+        label_path = labels_dir / (img_path.stem + '.txt')
+        
+        with open(label_path, 'w') as f:
+            for ann in anns:
+                if ann['category_id'] == 0:
+                    continue
+                
+                cat_id = ann['category_id']
+                bbox = ann['bbox']
+                x, y, w, h = bbox
+                
+                x_center = x + w / 2
+                y_center = y + h / 2
+                
+                img_w = img_info['width']
+                img_h = img_info['height']
+                
+                x_center /= img_w
+                y_center /= img_h
+                w /= img_w
+                h /= img_h
+                
+                f.write(f"{cat_id} {x_center:.6f} {y_center:.6f} {w:.6f} {h:.6f}\n")
+                total_boxes += 1
+    
+    print(f"Generated {total_boxes} bounding boxes in {labels_dir}")
+    print(f"Labels saved to: {labels_dir}")
+
+if __name__ == "__main__":
+    base_dir = Path(r"C:\Users\16337\PycharmProjects\Security\datasets\coco")
+    
+    generate_coco_labels(
+        annotations_file=base_dir / "annotations" / "instances_val2017.json",
+        images_dir=base_dir / "images" / "val2017",
+        labels_dir=base_dir / "labels" / "val2017"
+    )
+    
+    print("\nNow run validation with batch=1:")
+    print('yolo val model=yolo11n_int8_b1_8.engine data=coco.yaml imgsz=640 rect=False batch=1')