Update app.py

app.py

@@ -1,7 +1,6 @@
 import torch
 from transformers import BlipProcessor, BlipForConditionalGeneration
 from PIL import Image
-from RealESRGAN import RealESRGAN
 import gradio as gr
 import numpy as np
 import tempfile
@@ -10,102 +9,33 @@ import os
 # Set device to GPU if available, otherwise use CPU
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 
-# Load the BLIP model and processor once
+# Load the BLIP model and processor
 processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
 model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base").to(device)
 
-# Load the Real-ESRGAN models
-model2 = RealESRGAN(device, scale=2)
-model4 = RealESRGAN(device, scale=4)
-model8 = RealESRGAN(device, scale=8)
-
-# Load weights for all models at the start to avoid reloading during processing
-model2.load_weights('weights/RealESRGAN_x2.pth', download=True)
-model4.load_weights('weights/RealESRGAN_x4.pth', download=True)
-model8.load_weights('weights/RealESRGAN_x8.pth', download=True)
-
-# Function to enhance image resolution
-def enhance_image(image, scale):
-    image_np = np.array(image.convert('RGB'))
-    if scale == '2x':
-        result = model2.predict(image_np)
-    elif scale == '4x':
-        result = model4.predict(image_np)
-    else:
-        result = model8.predict(image_np)
-    return Image.fromarray(np.uint8(result))
-
 # Function to generate caption for the image using BLIP
 def generate_caption(image):
     inputs = processor(images=image, return_tensors="pt").to(device)
     output_ids = model.generate(**inputs)
     return processor.decode(output_ids[0], skip_special_tokens=True)
 
-# Function to adjust DPI of the image
-def muda_dpi(image, dpi):
-    image.save(image.filename, format='JPEG', dpi=(dpi, dpi))
-    return image
-
-# Function to resize the image
-def resize_image(image, width, height):
-    return image.resize((width, height))
-
-# Main function to process images
-def process_images(image_files, enhance, scale, adjust_dpi, dpi, resize, width, height):
-    processed_images = []
-    file_paths = []
+# Function to process images and generate captions
+def process_images(image_files):
     captions = []
-    
-    for i, image_file in enumerate(image_files):
+    for image_file in image_files:
         image = Image.open(image_file).convert('RGB')
-        
-        # Enhance resolution if required
-        if enhance:
-            image = enhance_image(image, scale)
-        
-        # Adjust DPI if required
-        if adjust_dpi:
-            image = muda_dpi(image, dpi)
-        
-        # Resize if required
-        if resize:
-            image = resize_image(image, width, height)
-        
-        # Generate caption
         caption = generate_caption(image)
         captions.append(caption)
-        
-        # Save the processed image
-        custom_filename = f"Image_Captioning_with_BLIP_{i+1}.jpg"
-        temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.jpg')
-        image.save(temp_file.name, format='JPEG')
-        final_path = temp_file.name.replace(temp_file.name.split('/')[-1], custom_filename)
-        os.rename(temp_file.name, final_path)
-        file_paths.append(final_path)
-        processed_images.append(image)
-    
-    return processed_images, file_paths, captions
+    return captions
 
 # Setup Gradio interface
 iface = gr.Interface(
     fn=process_images,
-    inputs=[
-        gr.Files(label="Upload Image Files"),
-        gr.Checkbox(label="Enhance Images (ESRGAN)"),
-        gr.Radio(['2x', '4x', '8x'], type="value", value='2x', label='Resolution model'),
-        gr.Checkbox(label="Adjust DPI"),
-        gr.Number(label="DPI", value=300),
-        gr.Checkbox(label="Resize"),
-        gr.Number(label="Width", value=512),
-        gr.Number(label="Height", value=512)
-    ],
-    outputs=[
-        gr.Gallery(label="Final Images"),
-        gr.Files(label="Download Final Images"),
-        gr.Textbox(label="Image Captions")
-    ],
-    title="High-Quality Image Enhancer with Fast Processing",
-    description="Upload multiple images (.jpg, .png), enhance using AI, adjust DPI, resize, generate captions, and download the final results."
+    inputs=[gr.Files(label="Upload Image Files")],
+    outputs=[gr.Textbox(label="Image Captions")],
+    title="Image Captioning with BLIP",
+    description="Upload images and generate captions using the BLIP model from Hugging Face."
 )
 
 iface.launch(debug=True)
+