Update src / streamlit_app.py

src / streamlit_app.py

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+import streamlit as st
+from PIL import Image
+import cv2
+import numpy as np
+import os
+from zipfile import ZipFile
+
+# Title and description of the app
+st.title("Image Processing App - Image Augmentations")
+st.markdown("""
+Upload an image to perform augmentations such as translation, scaling, rotation, cropping, and shearing. 
+Ten augmented images will be generated, and you can download them.
+""")
+
+# Upload an image
+uploaded_image = st.file_uploader("Upload an Image", type=["jpg", "jpeg", "png"])
+
+if uploaded_image is not None:
+    # Load and display the uploaded image
+    img = Image.open(uploaded_image)
+    img_array = np.array(img)
+    st.image(img, caption="Uploaded Image", use_column_width=True)
+
+    # Prepare the output directory for augmented images
+    output_dir = "augmented_images"
+    os.makedirs(output_dir, exist_ok=True)
+
+    # Define augmentations
+    st.write("**Performing augmentations...**")
+    transformations = [
+        ("Translated", cv2.warpAffine(img_array, np.float32([[1, 0, 50], [0, 1, 50]]), (img_array.shape[1], img_array.shape[0]))),
+        ("Scaled", cv2.resize(img_array, None, fx=1.2, fy=1.2)),
+        ("Rotated", cv2.warpAffine(img_array, cv2.getRotationMatrix2D((img_array.shape[1] // 2, img_array.shape[0] // 2), 45, 1), (img_array.shape[1], img_array.shape[0]))),
+        ("Cropped", img_array[50:img_array.shape[0] - 50, 50:img_array.shape[1] - 50]),
+        ("Sheared", cv2.warpAffine(img_array, np.float32([[1, 0.5, 0], [0.5, 1, 0]]), (img_array.shape[1], img_array.shape[0])))
+    ]
+
+    # Apply and save augmentations
+    augmented_images = []
+    for i, (name, aug_img) in enumerate(transformations * 2):  # Duplicate to generate 10 images
+        output_path = os.path.join(output_dir, f"aug_{i + 1}_{name}.jpg")
+        cv2.imwrite(output_path, aug_img)
+        augmented_images.append(output_path)
+
+    st.write("**Augmentation completed!**")
+
+    # Display augmented images
+    st.image([Image.open(img_path) for img_path in augmented_images], caption=[f"Image {i + 1}" for i in range(10)], width=150)
+
+    # Create a ZIP file for download
+    zip_filename = "augmented_images.zip"
+    with ZipFile(zip_filename, 'w') as zipf:
+        for file_path in augmented_images:
+            zipf.write(file_path, os.path.basename(file_path))
+
+    # Add a download button for the ZIP file
+    with open(zip_filename, "rb") as fp:
+        st.download_button(
+            label="Download Augmented Images",
+            data=fp,
+            file_name="augmented_images.zip",
+            mime="application/zip"
+        )