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app.py

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+#Part 2: adapted from our student's submission: https://huggingface.co/spaces/Halima/Homework02_part2
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import gradio as gr
+from scipy.ndimage.interpolation import shift
+from scipy import ndimage
+
+import tensorflow as tf
+
+#step 1: load the dataset
+(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()
+
+
+#step 2: Define input components on Gradio
+
+input_module1 = gr.inputs.Image(label = "test_image", image_mode='L', shape = (28,28))
+
+input_module2 = gr.inputs.Dropdown(choices=["shift up", "shift down", "shift left", "shift right", "rotate left", "rotate right"], label = "Augmentation")
+
+
+#step 3: Define output components on Gradio
+output_module1 = gr.outputs.Image(label = "Augmented Image")
+
+
+#step 4: Define functions for Gradio to use
+def image_movement(input1, input2):
+    
+    if input2 == 'shift up':
+        digit_image_u = shift(input1, [-5, 0], cval=0)
+        plt.imshow(digit_image_u,interpolation="nearest", cmap='gray')
+        plt.axis('off')
+        plt.savefig('testing.png')
+
+    elif input2 == 'shift down':
+        digit_image_d = shift(input1, [+5, 0], cval=0)
+        plt.imshow(digit_image_d,interpolation="nearest", cmap='gray')
+        plt.axis('off')
+        plt.savefig('testing.png')
+
+    elif input2 == 'shift left':
+        digit_image_l = shift(input1, [0, -5], cval=0)
+        plt.imshow(digit_image_l,interpolation="nearest", cmap='gray')
+        plt.axis('off')
+        plt.savefig('testing.png')
+
+    elif input2 == 'shift right':
+        digit_image_r = shift(input1, [0, +5], cval=0)
+        plt.imshow(digit_image_r,interpolation="nearest", cmap='gray')
+        plt.axis('off')
+        plt.savefig('testing.png')
+
+    elif input2 == 'rotate left':
+        rotate_image_right = ndimage.rotate(input1, 20, reshape=False)
+        plt.imshow(rotate_image_right,interpolation="nearest", cmap='gray')
+        plt.axis('off')
+        plt.savefig('testing.png')
+
+    else:
+        rotate_image_left = ndimage.rotate(input1, -20, reshape=False)
+        plt.imshow(rotate_image_left,interpolation="nearest", cmap='gray')
+        plt.axis('off')
+        plt.savefig('testing.png')
+
+    return 'testing.png'
+    
+    
+ 
+
+
+# Step 5: generate several example cases
+def get_sample_images(num_images):
+    sample_images = []
+    for i in range(num_images):
+      test_feature = x_test[i]
+      test_feature_2d =test_feature.reshape(28,28)
+    
+      # Make it unsigned integers:
+      data = test_feature_2d.astype(np.uint8)
+
+      sample_images.append([data,int(np.random.choice(['shift up', 'shift down', 'shift left', 'shift right', 'rotate left', 'rotate right']))])   # ["image path", "K"]
+    return sample_images
+    
+sample_images = get_sample_images(10)
+
+
+            
+ # Step 6: Put all three component together into the gradio's interface function 
+gr.Interface(fn=image_movement, 
+             inputs=[input_module1, input_module2], 
+             outputs=[output_module1],
+             examples_per_page = 2,
+             examples = sample_images, 
+             title="CSCI4750/5750 Homework02-Part II: Image Rotation", 
+             description= "Click examples below for a quick demo",
+             theme = 'huggingface',
+             layout = 'vertical'
+             
+            ).launch(debug = True)