Update app.py

app.py

@@ -77,18 +77,7 @@ model = AutoModel.from_pretrained(
 model = model.eval()
 print("✅ Model loaded successfully.")
 
-# --- Helper function to find pre-generated result images ---
-def find_result_image(path):
-    for filename in os.listdir(path):
-        if "grounding" in filename or "result" in filename:
-            try:
-                image_path = os.path.join(path, filename)
-                return Image.open(image_path)
-            except Exception as e:
-                print(f"Error opening result image {filename}: {e}")
-    return None
-
-# --- 2. Main Processing Function (UPDATED for multi-bbox drawing) ---
+# --- 2. Main Processing Function (UPDATED) ---
 def process_ocr_task(image, model_size, task_type):
     """
     Processes an image with DeepSeek-OCR for all supported tasks.
@@ -149,7 +138,7 @@ def process_ocr_task(image, model_size, task_type):
         return text_result
 
 # --- 3. Build the Gradio Interface (UPDATED) ---
-with gr.Blocks(title="DeepSeek-OCR X (t)", theme=gr.themes.Soft()) as demo:
+with gr.Blocks(title="DeepSeek-OCR X (t)", theme=gr.themes.Monochrome()) as demo:
     gr.Markdown(
         """
         # DeepSeek-OCR X TUL
@@ -168,12 +157,11 @@ with gr.Blocks(title="DeepSeek-OCR X (t)", theme=gr.themes.Soft()) as demo:
         with gr.Column(scale=1):
             image_input = gr.Image(type="pil", label="🖼️ Upload Image", sources=["upload", "clipboard"])
             model_size = gr.Dropdown(choices=["Tiny", "Small", "Base", "Large", "Gundam (Recommended)"], value="Gundam (Recommended)", label="⚙️ Resolution Size")
-            task_type = gr.Dropdown(choices=["📝 Free OCR", "📄 Convert to Markdown", "📈 Parse Figure"], value="📄 Convert to Markdown", label="🚀 Task Type")
+            task_type = gr.Dropdown(choices=["📝 Free OCR", "📄 Convert to Markdown", "📈 Parse Figure"], value="📝 Free OCR", label="🚀 Task Type")
             submit_btn = gr.Button("Process Image", variant="primary")
 
         with gr.Column(scale=2):
             output_text = gr.Textbox(label="📄 Text Result", lines=15, show_copy_button=True)
-            output_image = gr.Image(label="🖼️ Image Result (if any)", type="pil")
 
     submit_btn.click(fn=process_ocr_task, inputs=[image_input, model_size, task_type], outputs=[output_text])