Update README.md

README.md

@@ -1,3 +1,69 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- open-thoughts/OpenThoughts-114k
+language:
+- aa
+metrics:
+- accuracy
+base_model:
+- deepseek-ai/DeepSeek-R1
+new_version: deepseek-ai/DeepSeek-R1
+pipeline_tag: image-to-image
+library_name: adapter-transformers
+---
+import cv2
+import numpy as np
+import torch
+from basicsr.archs.rrdbnet_arch import RRDBNet
+from realesrgan import RealESRGANer
+from gfpgan import GFPGANer
+
+class ImageRestorer:
+    def __init__(self, device='cuda'):
+        # 初始化设备
+        self.device = torch.device(device)
+        
+        # 加载超分辨率模型
+        self.upsampler = RealESRGANer(
+            scale=4,
+            model_path='weights/RealESRGAN_x4plus.pth',
+            model=RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32),
+            tile=400,
+            tile_pad=10,
+            pre_pad=0,
+            half=True
+        )
+
+        # 加载面部增强模型
+        self.face_enhancer = GFPGANer(
+            model_path='weights/GFPGANv1.4.pth',
+            upscale=4,
+            arch='clean',
+            channel_multiplier=2,
+            bg_upsampler=self.upsampler
+        )
+
+    def restore_image(self, input_path, output_path, face_enhance=True):
+        # 读取图像
+        img = cv2.imread(input_path, cv2.IMREAD_UNCHANGED)
+        
+        try:
+            if face_enhance:
+                # 执行面部增强
+                _, _, output = self.face_enhancer.enhance(
+                    img,
+                    has_aligned=False,
+                    only_center_face=False,
+                    paste_back=True
+                )
+            else:
+                # 普通超分辨率处理
+                output, _ = self.upsampler.enhance(img, outscale=4)
+            
+            # 保存结果
+            cv2.imwrite(output_path, output)
+            print(f"图像已保存至 {output_path}")
+            
+        except Exception as e:
+            print(f"处理出错: {e}")