Update app.py

app.py

@@ -1,9 +1,9 @@
-import numpy as np
-
-if not hasattr(np, 'sctypes'):
-    np.sctypes = {
-        "float": [np.float16, np.float32, np.float64],
-        "int": [np.int8, np.int16, np.int32, np.int64]
+# Define basic float and int types to patch sctypes without numpy
+if not hasattr(__builtins__, 'sctypes'):
+    sctypes = {
+        "float": [float],
+        "int": [int],
+        "uint": [int]  # Handle 'uint' as normal 'int' since it's not natively supported without numpy
     }
 
 # Now, import imgaug after patching
@@ -13,23 +13,24 @@ import matplotlib.pyplot as plt
 import gradio as gr
 
 def augment_image(image, flip, rotate, brightness, noise_scale, elastic_alpha, elastic_sigma):
+    # Ensure the image is a NumPy array (required by imgaug)
     image = np.array(image)
     
-    # apply augs based on user inputs
+    # Apply augmentations based on user inputs
     if flip:
         flip_aug = iaa.Fliplr(1.0)  # flips horizontally 100% of the time
         image = flip_aug.augment_image(image)
 
-    rotate_aug = iaa.Affine(rotate=rotate)  # rotate by specified degrees
+    rotate_aug = iaa.Affine(rotate=rotate)  # Rotate by specified degrees
     image = rotate_aug.augment_image(image)
 
-    brightness_aug = iaa.Multiply(brightness)  # adjust brightness
+    brightness_aug = iaa.Multiply(brightness)  # Adjust brightness
     image = brightness_aug.augment_image(image)
 
     noise_aug = iaa.AdditiveGaussianNoise(scale=(noise_scale))  # Gaussian noise
     image = noise_aug.augment_image(image)
 
-    elastic_aug = iaa.ElasticTransformation(alpha=elastic_alpha, sigma=elastic_sigma)  # elastic transformation
+    elastic_aug = iaa.ElasticTransformation(alpha=elastic_alpha, sigma=elastic_sigma)  # Elastic transformation
     image = elastic_aug.augment_image(image)
     
     return image
@@ -38,6 +39,7 @@ def gradio_interface(image, flip, rotate, brightness, noise_scale, elastic_alpha
     augmented_image = augment_image(image, flip, rotate, brightness, noise_scale, elastic_alpha, elastic_sigma)
     return augmented_image
 
+# Gradio UI
 inputs = [
     gr.Image(type="pil"),  # Image input
     gr.Checkbox(label="Flip Image Horizontally"),  # Flip input