update page

app.py

@@ -48,10 +48,6 @@ output_dir="outputs"
 device = 'cuda'
 background_list = os.listdir('assets/backgrounds')
 
-#groundingdino_model = None
-#mam_predictor = None
-#generator = None
-
 # initialize MAM
 mam_model = networks.get_generator_m2m(seg='sam', m2m='sam_decoder_deep')
 mam_model.to(device)
@@ -68,31 +64,9 @@ generator.to(device)
 
 def run_grounded_sam(input_image, text_prompt, task_type, background_prompt, background_type, box_threshold, text_threshold, iou_threshold, scribble_mode, guidance_mode):
 
-    #global groundingdino_model, sam_predictor, generator
-
     # make dir
     os.makedirs(output_dir, exist_ok=True)
 
-    #if mam_predictor is None:
-        # initialize MAM
-        # build model
-    #    mam_model = networks.get_generator_m2m(seg='sam', m2m='sam_decoder_deep')
-    #    mam_model.to(device)
-
-        # load checkpoint
-    #    checkpoint = torch.load(mam_checkpoint, map_location=device)
-    #    mam_model.load_state_dict(utils.remove_prefix_state_dict(checkpoint['state_dict']), strict=True)
-
-        # inference
-    #    mam_model = mam_model.eval()
-
-    #if groundingdino_model is None:
-    #    grounding_dino_model = Model(model_config_path=GROUNDING_DINO_CONFIG_PATH, model_checkpoint_path=GROUNDING_DINO_CHECKPOINT_PATH, device=device)
-
-    #if generator is None:
-    #    generator = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16)
-    #    generator.to(device)
-
     # load image
     image_ori = input_image["image"]
     scribble = input_image["mask"]
@@ -245,8 +219,20 @@ if __name__ == "__main__":
     with block:
         gr.Markdown(
         """
-        # Matting Anything Demo
-        Welcome to the Matting Anything demo and upload your image to get started <br/> You may select different prompt types to get the alpha matte of target instance, and select different backgrounds for image composition.
+        # Matting Anything
+
+        [Jiachen Li](https://chrisjuniorli.github.io/),
+        [Jitesh Jain](https://praeclarumjj3.github.io/),
+        [Humphrey Shi](https://www.humphreyshi.com/home)
+
+        [[`Project page`](https://chrisjuniorli.github.io/project/Matting-Anything/)]
+        [[`ArXiv`](https://arxiv.org/abs/2306.05399)]
+        [[`Code`](https://github.com/SHI-Labs/Matting-Anything)]
+        [[`Video`](https://www.youtube.com/watch?v=XY2Q0HATGOk)]
+
+        Welcome to the Matting Anything demo and upload your image to get started <br/> 
+        You may select different prompt types to get the alpha matte of target instance, and select different backgrounds for image composition. The local setup instructions of the demo is available at: https://github.com/SHI-Labs/Matting-Anything
+
         ## Usage
         You may check the <a href='https://www.youtube.com/watch?v=XY2Q0HATGOk'>video</a> to see how to play with the demo, or check the details below.
         <details>
@@ -263,6 +249,9 @@ if __name__ == "__main__":
         **real_world_sample**: Randomly select a real-world image from `assets/backgrounds` for composition.
 
         **generated_by_text**: Send background text prompt to create a background image with stable diffusion model in the `Background prompt` box.
+
+        **guidance_mode**: Try mask guidance if alpha guidacne didn't return satisfying outputs
+
         </details>
         """)