Update app.py

app.py

@@ -8,7 +8,9 @@ import wget
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 # Load the models
+# Image captioning model to generate captions from uploaded images
 caption_image = pipeline("image-to-text", model="Salesforce/blip-image-captioning-large", device=device)
+# Stable Diffusion model for generating new images based on captions
 sd_pipeline = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5").to(device)
 
 # Load the translation model (English to Arabic)
@@ -19,9 +21,23 @@ translator = pipeline(
     device=device
 )
 
-# Download the image
-url1 = "https://github.com/Shahad-b/Image-database/blob/main/sea.jpg?raw=true"
-sea = wget.download(url1)
+# Function to generate images based on the image's caption
+def generate_image_and_translate(image, num_images=1):
+    # Generate caption in English from the uploaded image
+    caption_en = caption_image(image)[0]['generated_text']
+
+    # Translate the English caption to Arabic
+    caption_ar = translator(caption_en, src_lang="eng_Latn", tgt_lang="arb_Arab")[0]['translation_text']
+
+    generated_images = []
+
+    # Generate the specified number of images based on the English caption
+    for _ in range(num_images):
+        generated_image = sd_pipeline(prompt=caption_en).images[0]
+        generated_images.append(generated_image)
+
+    # Return the generated images along with both captions
+    return generated_images, caption_en, caption_ar
 
 # Function to generate images based on the image's caption
 def generate_image_and_translate(image, num_images=1):
@@ -43,24 +59,20 @@ def generate_image_and_translate(image, num_images=1):
 
 # Set up the Gradio interface
 interface = gr.Interface(
-    fn=generate_image_and_translate,
+    fn=generate_image_and_translate,   # Function to call when processing input
     inputs=[
-        gr.Image(type="pil", label="Upload Image"),
-        gr.Slider(minimum=1, maximum=10, label="Number of Images", value=1, step=1)
+        gr.Image(type="pil", label="📤 Upload Image"), # Input for image upload
+        gr.Slider(minimum=1, maximum=10, label="🔢 Number of Images", value=1, step=1) # Slider to select number of images
     ],
     outputs=[
-        gr.Gallery(label="Generated Images"),
-        gr.Textbox(label="Generated Caption (English)", interactive=False),
-        gr.Textbox(label="Translated Caption (Arabic)", interactive=False)
+        gr.Gallery(label="🖼️ Generated Images"),
+        gr.Textbox(label="📝 Generated Caption (English)", interactive=False),
+        gr.Textbox(label="🌍 Translated Caption (Arabic)", interactive=False)
     ],
-    title="Image Generation and Translation",
-    description="Upload an image to generate new images based on its caption and translate the caption into Arabic.",
-    examples=[
-        ["sea.jpg", 3]
-    ]
+    title="Image Generation and Captioning", # Title of the interface
+    description="Upload an image to extract a caption and display it in both Arabic and English. Then, a new image will be generated based on that caption.",  # Description
+    theme='freddyaboulton/dracula_revamped' # Determine theme
 )
 
 # Launch the Gradio application
-interface.launch()
-if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=7860)
+interface.launch()