add res , remove files

app.py

@@ -147,7 +147,7 @@ def cleanup_old_files():
             if current_time - file_path.stat().st_mtime > 3600:  # 1 hour
                 file_path.unlink()
 
-with gr.Blocks() as demo:
+with gr.Blocks(theme=gr.themes.Base()) as demo:
     with gr.Row():
         gr.Markdown(title)
     

content/index.md

@@ -1,53 +0,0 @@
----
-title: "🙋🏻‍♂️Welcome to Tonic's🫴🏻📸GOT-OCR"
----
-
-# GOT-OCR Model Overview
-
-The **GOT-OCR model** is a cutting-edge OCR system with **580M parameters**, designed to process a wide range of "characters." Equipped with a **high-compression encoder** and a **long-context decoder**, it excels in both scene and document-style images. The model supports **multi-page** and **dynamic resolution OCR**, enhancing its versatility.
-
-### Output Formats
-
-The model can generate results in several formats:
-
-- **Plain Text**
-- **Markdown**
-- **TikZ diagrams**
-- **Molecular SMILES strings**
-
-Additionally, **interactive OCR** enables users to define regions of interest via **coordinates** or **colors**.
-
-## Key Features
-
-- **Plain Text OCR**: Extracts text from images.
-- **Formatted Text OCR**: Retains the original formatting, including tables and formulas.
-- **Fine-grained OCR**: Offers box-based and color-based OCR for precision in specific regions.
-- **Multi-crop OCR**: Handles multiple cropped sections within an image.
-- **Rendered Formatted OCR**: Outputs in markdown, TikZ, SMILES, and more, with rendered formatting.
-
-## Supported Content Types
-
-- Plain text
-- Math/molecular formulas
-- Tables and charts
-- Sheet music
-- Geometric shapes
-
-## How to Use
-
-1. Select a task from the dropdown menu.
-2. Upload an image.
-3. (Optional) Adjust parameters based on the selected task.
-4. Click **Process** to view the results.
-
-### Model Information
-
-- **Model Name**: GOT-OCR 2.0
-- **Hugging Face Repository**: [ucaslcl/GOT-OCR2_0](https://huggingface.co/ucaslcl/GOT-OCR2_0)
-- **Environment**: CUDA 11.8 + PyTorch 2.0.1
-
----
-
-### Join us :
-
-🌟TeamTonic🌟 is always making cool demos! Join our active builder's 🛠️community 👻 [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/qdfnvSPcqP) On 🤗Huggingface:[MultiTransformer](https://huggingface.co/MultiTransformer) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [Build Tonic](https://git.tonic-ai.com/contribute)🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗

notes.py

@@ -1,92 +0,0 @@
-def ocr_demo(image, task, ocr_type, ocr_box, ocr_color):
-    res, html_content = process_image(image, task, ocr_type, ocr_box, ocr_color)
-    
-    res = f"$$ {res} $$"
-    # res = res.replace("$$ \\begin{tabular}", "\\begin{tabular}")
-    # res = res.replace("\\end{tabular} $$", "\\end{tabular}")
-    # res = res.replace("\\(", "")
-    # res = res.replace("\\)", "")
-    
-    if html_content:
-        html_string = f'<iframe srcdoc="{html_content}" width="100%" height="600px"></iframe>'
-        return res, html_string
-    return res, None
-
-@spaces.GPU
-def process_image(image, task, ocr_type=None, ocr_box=None, ocr_color=None):
-    demo_html = os.path.join(results_folder, "demo.html")
-    html_file = os.path.join(results_folder, f"{task.replace(' ', '_').lower()}.html")
-    tikz_file = os.path.join(results_folder, "tikz.html")
-    
-    unique_id = str(uuid.uuid4())
-    
-    with tempfile.NamedTemporaryFile(mode='w+', suffix='.html', delete=False, dir=results_folder) as temp_file:
-        temp_html_path = temp_file.name
-    
-    if task == "Plain Text OCR":
-        res = model.chat(tokenizer, image, ocr_type='ocr')
-        return res, None, unique_id
-    else:
-        if task == "Format Text OCR":
-            res = model.chat(tokenizer, image, ocr_type='format', render=True, save_render_file=temp_html_path)
-        elif task == "Fine-grained OCR (Box)":
-            res = model.chat(tokenizer, image, ocr_type=ocr_type, ocr_box=ocr_box, render=True, save_render_file=temp_html_path)
-        elif task == "Fine-grained OCR (Color)":
-            res = model.chat(tokenizer, image, ocr_type=ocr_type, ocr_color=ocr_color, render=True, save_render_file=temp_html_path)
-        elif task == "Multi-crop OCR":
-            res = model.chat_crop(tokenizer, image, ocr_type='format', render=True, save_render_file=temp_html_path)
-        elif task == "Render Formatted OCR":
-            res = model.chat(tokenizer, image, ocr_type='format', render=True, save_render_file=temp_html_path)
-        
-        # html_content = None
-        if os.path.exists(temp_html_path):
-            with open(temp_html_path, 'r') as f:
-                html_content = f.read()
-        if os.path.exists(demo_html):
-            with open(demo_html, 'r') as f:
-                html_content = f.read()
-        elif os.path.exists(html_file):
-            with open(html_file, 'r') as f:
-                html_content = f.read()
-        elif os.path.exists(tikz_file):
-            with open(tikz_file, 'r') as f:
-                html_content = f.read()
-        else:
-            html_content = None
-                
-        return res, html_content, unique_id
-
-@spaces.GPU
-def process_image(image, task, ocr_type=None, ocr_box=None, ocr_color=None):
-    demo_html = os.path.join(results_folder, "demo.html")
-    html_file = os.path.join(results_folder, f"{task.replace(' ', '_').lower()}.html")
-    tikz_file = os.path.join(results_folder, "tikz.html")
-    
-    if task == "Plain Text OCR":
-        res = model.chat(tokenizer, image, ocr_type='ocr')
-        return res, None
-    else:
-        if task == "Format Text OCR":
-            res = model.chat(tokenizer, image, ocr_type='format', render=True, save_render_file=demo_html)
-        elif task == "Fine-grained OCR (Box)":
-            res = model.chat(tokenizer, image, ocr_type=ocr_type, ocr_box=ocr_box, render=True, save_render_file=demo_html)
-        elif task == "Fine-grained OCR (Color)":
-            res = model.chat(tokenizer, image, ocr_type=ocr_type, ocr_color=ocr_color, render=True, save_render_file=demo_html)
-        elif task == "Multi-crop OCR":
-            res = model.chat_crop(tokenizer, image, ocr_type='format', render=True, save_render_file=demo_html)
-        elif task == "Render Formatted OCR":
-            res = model.chat(tokenizer, image, ocr_type='format', render=True, save_render_file=demo_html)
-        
-        if os.path.exists(demo_html):
-            with open(demo_html, 'r') as f:
-                html_content = f.read()
-        elif os.path.exists(html_file):
-            with open(html_file, 'r') as f:
-                html_content = f.read()
-        elif os.path.exists(tikz_file):
-            with open(tikz_file, 'r') as f:
-                html_content = f.read()
-        else:
-            html_content = None
-        
-        return res, html_content