add requirements

app.py

@@ -6,12 +6,12 @@ from app_canny import create_demo as create_demo_canny
 from app_depth import create_demo as create_demo_depth
 import os
 
-hf_hub_download('wondervictor/ControlAR',
+hf_hub_download(repo_id='wondervictor/ControlAR',
                 filename='canny_MR.safetensors',
-                cache_dir='./checkpoints/')
-hf_hub_download('wondervictor/ControlAR',
+                local_dir='./checkpoints/')
+hf_hub_download(repo_id='wondervictor/ControlAR',
                 filename='depth_MR.safetensors',
-                cache_dir='./checkpoints/')
+                local_dir='./checkpoints/')
 # hf_hub_download('google/flan-t5-xl', cache_dir='./checkpoints/')
 
 DESCRIPTION = "# [ControlAR: Controllable Image Generation with Autoregressive Models](https://arxiv.org/abs/2410.02705) \n ### The first row in outputs is the input image and condition. The second row is the images generated by ControlAR.  \n ### You can run locally by following the instruction on our [Github Repo](https://github.com/hustvl/ControlAR)."
@@ -32,4 +32,4 @@ with gr.Blocks(css="style.css") as demo:
             create_demo_canny(model.process_canny)
 
 if __name__ == "__main__":
-    demo.queue().launch(share=False, server_name="0.0.0.0")
+    demo.launch(share=False)

autoregressive/models/dinov2_adapter.py

@@ -10,7 +10,7 @@ class Dinov2_Adapter(nn.Module):
         super(Dinov2_Adapter, self).__init__()
         print(f"Choose adapter size: {adapter_size}")
         print(f"condition type: {condition_type}")
-        self.model = AutoModel.from_pretrained(f'autoregressive/models/dinov2-{adapter_size}')
+        self.model = AutoModel.from_pretrained(f'facebook/dinov2-{adapter_size}')
         self.condition_type = condition_type
     
     def to_patch14(self, input):

model.py

@@ -14,8 +14,8 @@ from autoregressive.models.generate import generate
 from condition.midas.depth import MidasDetector
 
 models = {
-    "canny": "checkpoints/t2i/canny_MR.safetensors",
-    "depth": "checkpoints/t2i/depth_MR.safetensors",
+    "canny": "checkpoints/canny_MR.safetensors",
+    "depth": "checkpoints/depth_MR.safetensors",
 }
 
 

requirements.txt

@@ -18,4 +18,5 @@ clean-fid
 safetensors
 transformers
 tiktoken
-sentencepiece
+sentencepiece
+basicsr