Update app.py

app.py

@@ -1,24 +1,19 @@
+# Import necessary libraries
 import os
 import tempfile
 import gradio as gr
 from dotenv import load_dotenv
 import torch
 from scipy.io.wavfile import write
-from diffusers import DiffusionPipeline
+from diffusers import DiffusionPipeline  
 import google.generativeai as genai
 from pathlib import Path
 
-# Check CUDA availability
-print(f"Is CUDA available: {torch.cuda.is_available()}")
-if torch.cuda.is_available():
-    print(f"CUDA device: {torch.cuda.get_device_name(torch.cuda.current_device())}")
-  else:
-    print("Using CPU as fallback.")
 
 # Load environment variables from .env file
 load_dotenv()
 
-# Google Generative AI for Gemini
+#Google Generative AI for Gemini
 genai.configure(api_key=os.getenv("API_KEY"))
 
 # Hugging Face token from environment variables
@@ -29,26 +24,22 @@ def analyze_image_with_gemini(image_file):
     Analyzes an uploaded image with Gemini and generates a descriptive caption.
     """
     try:
-        # Save uploaded image to a temporary file
+# Save uploaded image to a temporary file
         temp_image_path = tempfile.NamedTemporaryFile(delete=False, suffix=".jpg").name
         with open(temp_image_path, "wb") as temp_file:
             temp_file.write(image_file)
 
-        # Prepare the image data and prompt for Gemini
+# Prepare the image data and prompt for Gemini
         image_parts = [{"mime_type": "image/jpeg", "data": Path(temp_image_path).read_bytes()}]
         prompt_parts = ["Describe precisely the image in one sentence.\n", image_parts[0], "\n"]
         generation_config = {"temperature": 0.05, "top_p": 1, "top_k": 26, "max_output_tokens": 4096}
-        safety_settings = [
-            {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_MEDIUM_AND_ABOVE"},
-            {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_MEDIUM_AND_ABOVE"},
-            {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_MEDIUM_AND_ABOVE"},
-            {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_MEDIUM_AND_ABOVE"}
-        ]
-        model = genai.GenerativeModel(
-            model_name="gemini-1.0-pro-vision-latest",
-            generation_config=generation_config,
-            safety_settings=safety_settings
-        )
+        safety_settings = [{"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_MEDIUM_AND_ABOVE"},
+                           {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_MEDIUM_AND_ABOVE"},
+                           {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_MEDIUM_AND_ABOVE"},
+                           {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_MEDIUM_AND_ABOVE"}]
+        model = genai.GenerativeModel(model_name="gemini-1.0-pro-vision-latest",
+                                      generation_config=generation_config,
+                                      safety_settings=safety_settings)
         response = model.generate_content(prompt_parts)
         return response.text.strip(), False  # False indicates no error
     except Exception as e:
@@ -59,11 +50,11 @@ def get_audioldm_from_caption(caption):
     """
     Generates sound from a caption using the AudioLDM-2 model.
     """
-    # Initialize the model
+# Initialize the model
     pipe = DiffusionPipeline.from_pretrained("cvssp/audioldm2", use_auth_token=hf_token)
     pipe = pipe.to("cuda" if torch.cuda.is_available() else "cpu")
 
-    # Generate audio from the caption
+# Generate audio from the caption
     audio_output = pipe(prompt=caption, num_inference_steps=50, guidance_scale=7.5)
     audio = audio_output.audios[0]  
 
@@ -72,12 +63,13 @@ def get_audioldm_from_caption(caption):
 
     return temp_file.name
 
-# CSS
+# css
 css="""
 #col-container{
     margin: 0 auto;
     max-width: 800px;
-}
+    }
+
 """
 
 # Gradio interface setup
@@ -85,46 +77,44 @@ with gr.Blocks(css=css) as demo:
     # Main Title and App Description
     with gr.Column(elem_id="col-container"):
         gr.HTML("""
-        <h1 style="text-align: center;">
-            🎶 Generate Sound Effects from Image
+    <h1 style="text-align: center;">
+           🎶 Generate Sound Effects from Image
         </h1>
-        <p style="text-align: center;">
-            ⚡ Powered by <a href="https://bilsimaging.com" target="_blank">Bilsimaging</a>
+         <p style="text-align: center;">
+          ⚡  Powered by <a href="https://bilsimaging.com" _blank >Bilsimaging</a>
         </p>
-        """)
-
-        gr.Markdown("""
-        Welcome to this unique sound effect generator! This tool allows you to upload an image and generate a descriptive caption and a corresponding sound effect. Whether you're exploring the sound of nature, urban environments, or anything in between, this app brings your images to auditory life.
-
-        **💡 How it works:**
-        1. **Upload an image**: Choose an image that you'd like to analyze.
-        2. **Generate Description**: Click on 'Tap to Generate Description from the image' to get a textual description of your uploaded image.
-        3. **Generate Sound Effect**: Based on the image description, click on 'Generate Sound Effect' to create a sound effect that matches the image context.
-
-        Enjoy the journey from visual to auditory sensation with just a few clicks!
-
-        For example demos of sound effects generated, check out our [YouTube channel](https://www.youtube.com/playlist?list=PLwEbW4bdYBSC8exiJ9PfzufGND_14f--C).
-        """)
-
-    # Interface Components
+    """)
+    
+    gr.Markdown("""
+    Welcome to this unique sound effect generator! This tool allows you to upload an image and generate a descriptive caption and a corresponding sound effect. Whether you're exploring the sound of nature, urban environments, or anything in between, this app brings your images to auditory life.
+    
+    **💡 How it works:**
+    1. **Upload an image**: Choose an image that you'd like to analyze.
+    2. **Generate Description**: Click on 'Tap to Generate Description from the image' to get a textual description of your uploaded image.
+    3. **Generate Sound Effect**: Based on the image description, click on 'Generate Sound Effect' to create a sound effect that matches the image context.
+    
+    Enjoy the journey from visual to auditory sensation with just a few clicks!
+    
+    For Example Demos sound effects generated , check out our [YouTube channel](https://www.youtube.com/playlist?list=PLwEbW4bdYBSC8exiJ9PfzufGND_14f--C)
+    """)
+    
+# Interface Components
     image_upload = gr.File(label="Upload Image", type="binary")
     generate_description_button = gr.Button("Tap to Generate a Description from your image")
-    caption_display = gr.Textbox(label="Image Description", interactive=False)  # Read-only
+    caption_display = gr.Textbox(label="Image Description", interactive=False)  # Keep as read-only
     generate_sound_button = gr.Button("Generate Sound Effect")
     audio_output = gr.Audio(label="Generated Sound Effect")
-
-    # Extra footer
+# extra footer
     gr.Markdown("""## 👥 How You Can Contribute
         We welcome contributions and suggestions for improvements. Your feedback is invaluable to the continuous enhancement of this application. 
-
+                
         For support, questions, or to contribute, please contact us at [contact@bilsimaging.com](mailto:contact@bilsimaging.com).
-
+                
         Support our work and get involved by donating through [Ko-fi](https://ko-fi.com/bilsimaging). - Bilel Aroua
-        """)
+            """)
     gr.Markdown("""## 📢 Stay Connected
-        This app is a testament to the creative possibilities that emerge when technology meets art. Enjoy exploring the auditory landscape of your images!
-        """)
-
+        this app is a testament to the creative possibilities that emerge when technology meets art. Enjoy exploring the auditory landscape of your images!
+            """)
     # Function to update the caption display based on the uploaded image
     def update_caption(image_file):
         description, _ = analyze_image_with_gemini(image_file)
@@ -147,5 +137,7 @@ with gr.Blocks(css=css) as demo:
         outputs=audio_output
     )
 
+
+
 # Launch the Gradio app
-demo.launch(debug=True, share=True)
+demo.launch(debug=True, share=True)