paper published had to be added to the page

CLIP/clip.py

@@ -119,7 +119,7 @@ def load(name: str, device: Union[str, torch.device] = "cuda" if torch.cuda.is_a
         state_dict = torch.load(model_path, map_location="cpu")
 
     if not jit:
-        print("Heree.....")
+        # print("Heree.....")
         model = build_model(state_dict or model.state_dict()).to(device)
         if str(device) == "cpu":
             model.float()

MED_VQA_Huggyface_Gradio.py

@@ -155,9 +155,9 @@ def infer_answer_question(image, text):
     return cap_result
 
 
-image = gr.inputs.Image(type="pil")
-question = gr.inputs.Textbox(label="Question")
-answer = gr.outputs.Textbox(label="Predicted answer")
+image = gr.Image(type="pil")
+question = gr.Textbox(label="Question")
+answer = gr.Textbox(label="Predicted answer")
 examples = [["train_0000.jpg", "Where are liver stem cells (oval cells) located?"],
             ["train_0001.jpg", "What are stained here with an immunohistochemical stain for cytokeratin 7?"],
             ["train_0002.jpg", "What are bile duct cells and canals of Hering stained here with for cytokeratin 7?"],
@@ -165,10 +165,11 @@ examples = [["train_0000.jpg", "Where are liver stem cells (oval cells) located?
             ["train_0018.jpg", "Is there an infarct in the brain hypertrophy?"],
             ["train_0019.jpg", "What is ischemic coagulative necrosis?"]]
 
-title = "Interactive Visual Question Answering demo(BigMed@ai: Artificial Intelligence for Large-Scale Medical Image Analysis)"
-description = "<div style='display: flex;align-items: center;justify-content: space-between;'><p style='width:60vw;'>Gradio Demo for VQA medical model trained on PathVQA dataset, To use it, upload your image and type a question and click 'submit', or click one of the examples to load them.</p><a href='https://github.com/dandelin/ViLT' target='_blank' class='link'><img src='file/GitHub.png' style='justify-self:margin-top:0.5em;center; width:calc(200px + 5vw);'></a></div>"
+title = "Vision–Language Model for Visual Question Answering in Medical Imagery"
+description = "Gradio Demo for VQA medical model trained on PathVQA dataset, To use it, upload your image and type a question and click 'submit', or click one of the examples to load them.<br>" \
+              "You can access the paper <a href='https://www.mdpi.com/2306-5354/10/3/380' target='_blank'> Vision–Language Model for Visual Question Answering in Medical Imagery</a>. Y Bazi, MMA Rahhal, L Bashmal, M Zuair - Bioengineering, 2023"
 ### link to paper and github code
-article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2102.03334' target='_blank'>BigMed@ai</a> | <a href='https://github.com/dandelin/ViLT' target='_blank'>Github Repo</a></p>"
+article = "<p style='text-align: center'><a href='https://www.mdpi.com/2306-5354/10/3/380' target='_blank'>BigMed@ai</a></p>"
 
 interface = gr.Interface(fn=infer_answer_question,
                          inputs=[image, question],
@@ -176,6 +177,5 @@ interface = gr.Interface(fn=infer_answer_question,
                          examples=examples,
                          title=title,
                          description=description,
-                         article=article,
-                         enable_queue=True)
-interface.launch(debug=True)
+                         article=article)
+interface.launch(debug=True, enable_queue=True)

README.md

@@ -1,5 +1,5 @@
 ---
-title: VQA Demo
+title: Visual Question Answering in Medical Imagery
 emoji: 🧑‍⚕️
 colorFrom: yellow
 colorTo: red