Update app.py

app.py

@@ -9,20 +9,21 @@ HF_TOKEN = os.getenv("HF_TOKEN")
 SUBMISSIONS_REPO = "oddadmix/ocr-competition-submissions"
 RESULTS_REPO = "oddadmix/ocr-competition-results"
 
-def validate_fields(team_name, email, model_name, hf_model_id, hf_token):
+def validate_fields(team_name, email, model_name, hf_model_id, hf_token, code):
     # Check if any field is empty
-    if not team_name or not email or not model_name or not hf_model_id or not hf_token:
+    if not team_name or not email or not model_name or not hf_model_id or not hf_token or not code:
         return "All fields are required. Please fill in all fields."
     # Proceed with submission if all fields are filled
-    return submit(team_name, email, model_name, hf_model_id, hf_token)
+    return submit(team_name, email, model_name, hf_model_id, hf_token, code)
 
-def submit(team_name, email, model_name, hf_model_id, hf_token):
+def submit(team_name, email, model_name, hf_model_id, hf_token, code):
     entry = {
         "team_name": team_name,
         "email": email,
         "model_name": model_name,
         "hf_model_id": hf_model_id,
-        "hf_token": hf_token
+        "hf_token": hf_token,
+        "code": code
     }
     filename = f"{team_name}_{model_name}_{pd.Timestamp.now().strftime('%Y%m%d%H%M%S')}.json"
     with open(filename, "w") as f:
@@ -47,22 +48,78 @@ def show_results():
         return f"An error occurred while loading the results: {e}"
 
 with gr.Blocks() as demo:
-    gr.Markdown("# VLM OCR Competition Submission")
-    
-    with gr.Row():
-        team = gr.Textbox(label="Team Name")
-        email = gr.Textbox(label="Email")
-    model = gr.Textbox(label="Model Name")
-    hf_model = gr.Textbox(label="Hugging Face Model ID")
-    hf_token = gr.Textbox(label="Hugging Face Access Token", type="password")
-    
-    submit_btn = gr.Button("Submit")
-    status = gr.Textbox(label="Status")
-    
-    submit_btn.click(fn=validate_fields, inputs=[team, email, model, hf_model, hf_token], outputs=status)
-    
-    gr.Markdown("## Leaderboard Results")
-    results = gr.Dataframe(headers=["model_name", "WER", "CER", "BLEU", "team_name"])
-    demo.load(fn=show_results, outputs=results)
-    
+    gr.Markdown("# 🏆 VLM OCR Competition")
+
+    with gr.Tabs():
+        with gr.Tab("📜 Rules"):
+            gr.Markdown("""
+            ## Competition Rules
+            - Each team can submit **one model evaluation per week**.
+            - The competition runs from **September 12 to October 12** (1 month).
+            - The evaluation dataset will **not be provided** to participants.
+            - Teams must submit:
+              1. Their Hugging Face Model ID.
+              2. A valid Hugging Face token with access.
+              3. The code required to run the model.
+            - **Team name must remain the same across all submissions.**
+
+            ---
+            ### Sponsored & Organized By
+            <div style="display:flex; align-items:center; gap:20px;">
+                <div>
+                    <a href="https://www.linkedin.com/company/68577545" target="_blank">
+                        <img src="https://kand.ca/logo.png" alt="KANDCA" width="180"/>
+                    </a>
+                    <p><b>KANDCA</b> – Sponsor</p>
+                </div>
+                <div>
+                    <img src="https://kand.nyc3.cdn.digitaloceanspaces.com/namaa/namaa-logo.png" alt="NAMAA Community" width="180"/>
+                    <p><b>NAMAA Community</b> – Organizer</p>
+                </div>
+            </div>
+            """)
+
+        with gr.Tab("🎁 Prizes"):
+            gr.Markdown("""
+            ## Prize Distribution
+            - **1st Place:** 🥇 250 USD (bank transfer or API credits)  
+            - **2nd Place:** 🥈 125 USD  
+            - **3rd Place:** 🥉 75 USD  
+            - **4th Place:** 🎖️ 50 USD  
+            - **5th Place:** 🎖️ 25 USD  
+            """)
+
+        with gr.Tab("📊 Evaluation"):
+            gr.Markdown("""
+            ## Evaluation Details
+            - The evaluation dataset will remain **private**.
+            - It will include:
+              - Historical documents
+              - Scanned pages
+              - Different layouts
+              - Handwritten pages
+            - Models will be evaluated on **accuracy metrics** such as WER, CER, and BLEU.
+            """)
+
+        with gr.Tab("🚀 Submit & Leaderboard"):
+            gr.Markdown("### Submit Your Model")
+            with gr.Row():
+                team = gr.Textbox(label="Team Name")
+                email = gr.Textbox(label="Email")
+            model = gr.Textbox(label="Model Name")
+            hf_model = gr.Textbox(label="Hugging Face Model ID")
+            hf_token = gr.Textbox(label="Hugging Face Access Token", type="password")
+            code = gr.Textbox(label="Code (instructions to run your model)", lines=6, placeholder="Paste your run code here...")
+
+            submit_btn = gr.Button("Submit")
+            status = gr.Textbox(label="Status")
+
+            submit_btn.click(fn=validate_fields,
+                             inputs=[team, email, model, hf_model, hf_token, code],
+                             outputs=status)
+
+            gr.Markdown("### Leaderboard Results")
+            results = gr.Dataframe(headers=["model_name", "WER", "CER", "BLEU", "team_name"])
+            demo.load(fn=show_results, outputs=results)
+
     demo.launch()