Update app.py

app.py

@@ -1,45 +1,28 @@
 import gradio as gr
-from tensorflow.keras.preprocessing.image import img_to_array, ImageDataGenerator
-from PIL import Image
 import numpy as np
-import os
-import zipfile
-import io
+import time
 
-# Image Augmentation Function
-def augment_images(image_files, num_duplicates):
-    datagen = ImageDataGenerator(
-        rotation_range=40,
-        width_shift_range=0.2,
-        height_shift_range=0.2,
-        zoom_range=0.2,
-        fill_mode='nearest')
+def sepia(input_img, num_copies):
+    sepia_filter = np.array([
+        [0.393, 0.769, 0.189], 
+        [0.349, 0.686, 0.168], 
+        [0.272, 0.534, 0.131]
+    ])
+    # 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)
+    
+    # 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)
 
-    augmented_images = []
-    for image_file in image_files:
-        try:
-            img = Image.open(image_file).convert('RGB')
-            img = img.resize((256, 256))
-            x = img_to_array(img)
-            x = x.reshape((1,) + x.shape)
-            i = 0
-            for _ in datagen.flow(x, batch_size=1):
-                i += 1
-                augmented_images.append(x[0])
-                if i >= num_duplicates:
-                    break
-        except Exception as e:
-            print(f"Error processing image: {e}")
+demo = gr.Interface(fn=sepia,
+                    inputs=[gr.Image(), gr.Number(label="Number of Copies", default=1)],
+                    outputs=gr.Image(type="numpy", label="Sepia Image"),
+                    title="Sepia Tone Generator")
 
-    return augmented_images
-
-# Gradio UI
-demo = gr.Interface(
-    fn=augment_images,
-    inputs=gr.File(label="Upload Images", multiple=True, file_types=["jpg", "jpeg", "png"]),
-    outputs=gr.Image(label="Augmented Images"),
-    examples=[["images/cat.jpg"], ["images/dog.jpg"]],
-    description="Image Augmentation App",
-    allow_flagging=False)
-
-demo.launch()
+if __name__ == "__main__":
+    demo.launch()