feat: shifting to train yolo11 ✅

data_preprocess.py

@@ -44,7 +44,7 @@
             # 过滤非cat目标
             cat_results = list(filter(lambda target: target["name"] == "cat", results))
             # 跳过图片内检测不到cat或有多个cat的图片
-            if len(cat_results) != 1:
+            if len(cat_results) == 0:
                 num_skipped_photos += 1
                 continue
             # 裁剪出cat

data_split.py

@@ -3,6 +3,8 @@
 from sklearn.model_selection import train_test_split
 import argparse
 import json
+import random
+import shutil
 
 parser = argparse.ArgumentParser(description="Cat Recognize Data Preprocessor")
 parser.add_argument(
@@ -66,7 +68,7 @@ def resize_image(image_path, output_path, size):
     ]
 
     # 如果图片数量不足 args.filter，则进行补充
-    if len(images) < args.filter:
+    if len(images) != 0 and len(images) < args.filter:
         print(f"Category '{category}' has less than {args.filter} images. Augmenting...")
         while len(images) < args.filter:
             # 随机选择一张图片进行复制