Add example images

app.py

@@ -1,3 +1,5 @@
+import os
+import random
 import tensorflow as tf
 from keras import models
 import numpy as np
@@ -31,8 +33,7 @@ def preprocess_image(img):
 
 # Function to postprocess the image (denormalize)
 def postprocess_image(img):
-    img = cv2.cvtColor(((img + 1) * 127.5).numpy().astype(np.uint8), cv2.COLOR_LAB2RGB)
-    return np.uint8(np.clip(img, 0, 255))
+    return cv2.cvtColor(((img + 1) * 127.5).numpy().astype(np.uint8), cv2.COLOR_LAB2RGB)
 
 
 # Function to adjust brightness
@@ -94,12 +95,17 @@ def colorize_image(input_image):
 
 
 # Function to colorize and store the result for further manipulation
-def colorize_and_store(img):
+def colorize_and_store(img, bright_slider, cont_slider, sat_slider, hue_slider):
     # Colorize the image
     colorized_image = colorize_image(img)
 
+    output_image = adjust_brightness(colorized_image, bright_slider)
+    output_image = adjust_contrast(output_image, cont_slider)
+    output_image = adjust_saturation(output_image, sat_slider)
+    output_image = adjust_hue(output_image, hue_slider)
+
     # Return the colorized image for further manipulation (no model call)
-    return colorized_image, colorized_image
+    return colorized_image, output_image
 
 
 def make_grayscale_256(img):
@@ -133,6 +139,14 @@ p {
 }
 """
 
+# Get all image file paths in the folder
+image_files = [
+    os.path.join("examples", file)
+    for file in os.listdir("examples")
+    if file.lower().endswith((".png", ".jpg", ".jpeg", ".webp"))
+]
+random.shuffle(image_files)
+
 # Gradio Interface
 with gr.Blocks(css=css) as demo:
     demo.title = "Portrait Colorizer"
@@ -151,6 +165,9 @@ with gr.Blocks(css=css) as demo:
             width=256,
             elem_id="input-image",
         )
+        examples_gallery = gr.Examples(
+            examples=image_files, inputs=[input_image], label="Example Images"
+        )
         output_image = gr.Image(
             type="numpy",
             label="Colorized Image",
@@ -170,7 +187,7 @@ with gr.Blocks(css=css) as demo:
     # Button click triggers processing
     process_button.click(
         fn=colorize_and_store,
-        inputs=input_image,
+        inputs=[input_image, bright_slider, cont_slider, sat_slider, hue_slider],
         outputs=[colorized_image, output_image],
     )