Update app.py

app.py

@@ -1,36 +1,6 @@
 import gradio as gr
 import numpy as np
-from PIL import Image
-import random
-import tempfile
-import os
-from zipfile import ZipFile
-
-def apply_random_transformations(image):
-    # Randomly apply transformations: rotate, zoom, or add noise
-    transformations = [rotate_image, zoom_image, add_noise]
-    random.shuffle(transformations)  # Shuffle to apply them in random order
-    
-    for transform in transformations:
-        if random.choice([True, False]):  # Randomly decide whether to apply this transformation
-            image = transform(image)
-    return image
-
-def rotate_image(image):
-    angle = random.randint(-30, 30)  # Random angle
-    return image.rotate(angle)
-
-def zoom_image(image):
-    zoom_factor = random.uniform(0.9, 1.1)  # Random zoom factor
-    width, height = image.size
-    new_width = int(width * zoom_factor)
-    new_height = int(height * zoom_factor)
-    return image.resize((new_width, new_height), Image.LANCZOS)
-
-def add_noise(image_np):
-    noise = np.random.randn(*image_np.shape) * 25  # Adjust intensity as needed
-    noisy_image = np.clip(image_np + noise, 0, 255)
-    return Image.fromarray(noisy_image.astype(np.uint8))
+import time
 
 def sepia(input_img, num_copies):
     sepia_filter = np.array([
@@ -38,41 +8,21 @@ def sepia(input_img, num_copies):
         [0.349, 0.686, 0.168], 
         [0.272, 0.534, 0.131]
     ])
-    input_img = np.array(input_img) / 255.0
-    sepia_imgs = []
-    for _ in range(num_copies):
-        # Apply sepia filter
-        sepia_img = np.dot(input_img[..., :3], sepia_filter.T)
-        sepia_img = np.clip(sepia_img, 0, 1) * 255
-        img_pil = Image.fromarray(sepia_img.astype(np.uint8))
-
-        # Apply random transformations
-        img_transformed = apply_random_transformations(img_pil)
-        sepia_imgs.append(img_transformed)
+    # Normalize input image to 0-1 range
+    input_img = input_img / 255.0
+    sepia_img = np.dot(input_img[...,:3], sepia_filter.T)
+    sepia_img = np.clip(sepia_img, 0, 1)
     
-    return sepia_imgs
-
-def zip_sepia_images(sepia_imgs):
-    temp_dir = tempfile.mkdtemp()
-    zip_path = os.path.join(temp_dir, "sepia_images.zip")
-    with ZipFile(zip_path, 'w') as zipf:
-        for i, img in enumerate(sepia_imgs):
-            img_path = os.path.join(temp_dir, f"sepia_image_{i}.png")
-            img.save(img_path)
-            zipf.write(img_path, os.path.basename(img_path))
-    shutil.rmtree(temp_dir)  # Clean up after creating the ZIP
-    return zip_path
+    # Iterate to yield multiple sepia images
+    for _ in range(num_copies):
+        # Simulating a delay for demonstration, you might not need this
+        time.sleep(1)
+        yield (sepia_img * 255).astype(np.uint8)
 
-with gr.Blocks() as demo:
-    with gr.Row():
-        input_img = gr.Image()
-        num_copies = gr.Number(value=1)
-        gallery = gr.Gallery()
-        download_btn = gr.File()
-        
-    generate_btn = gr.Button("Generate Sepia Images")
-    generate_btn.click(fn=sepia, inputs=[input_img, num_copies], outputs=gallery)
-    generate_btn.click(fn=zip_sepia_images, inputs=gallery, outputs=download_btn)
+demo = gr.Interface(fn=sepia,
+                    inputs=[gr.Image(), gr.Number()],
+                    outputs="image",
+                    title="Sepia Tone Generator")
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()