Update app.py

app.py

@@ -1,17 +1,35 @@
 import os
 os.system("pip install git+https://github.com/facebookresearch/detectron2.git")
-os.system("pip install git+https://github.com/Visual-AI/Mr.DETR.git")
+os.system("git clone https://github.com/Visual-AI/Mr.DETR.git")
+os.system("cd Mr.DETR")
+os.system("pip install . && cd ..")
+
 
 import gradio as gr
+from demo.predictors import VisualizationDemo
+from detectron2.checkpoint import DetectionCheckpointer
+from detectron2.config import LazyConfig, instantiate
+import numpy as np
 
 if __name__ == "__main__":
     gr.close_all()
+    cfg = LazyConfig.load("Mr.DETR/projects/mr_detr_align/configs/deformable_detr_swinl_two_stage_12ep_plusplus.py")
+    model = instantiate(cfg.model)
+    checkpointer = DetectionCheckpointer(model)
+    checkpointer.load("https://huggingface.co/allencbzhang/Mr.DETR/blob/main/MrDETR_align_swinL_12ep_900q.pth")
+
+    model.eval()
+    vis_demo = VisualizationDemo(
+        model=model,
+        min_size_test=800,
+        max_size_test=1333,
+        img_format="RGB",
+        metadata_dataset="coco_2017_val",
+    )
     
     def inference(img, confidence):
-        print(type(img))  
-        return img
-        # img = np.array(img)
-        # _, results = vis_demo.run_on_image(img, confidence)
+        img = np.array(img)
+        _, results = vis_demo.run_on_image(img, confidence)
         return results 
     
     demo = gr.Interface(
@@ -21,9 +39,9 @@ if __name__ == "__main__":
             gr.Number(precision=2, minimum=0.0, maximum=1.0, value=0.5)
         ],
         outputs="image",
-        # examples=[
-        #     ["assets/000000014226.jpg"],
-        #     ["assets/000000028449.jpg"]
-        # ]
+        examples=[
+            ["Mr.DETR/assets/000000014226.jpg"],
+            ["Mr.DETR/assets/000000028449.jpg"]
+        ]
     )
-    demo.launch(share=True, debug=False)
+    demo.launch()