Update pages/8_Image_Augumentation.py

pages/8_Image_Augumentation.py

@@ -0,0 +1,92 @@
+import streamlit as st
+from PIL import Image
+import numpy as np
+import io
+import zipfile
+
+# Title of the app
+st.title("Image Transformation App")
+
+# Upload image files
+uploaded_files = st.file_uploader("Upload Images", type=["jpg", "jpeg", "png"], accept_multiple_files=True)
+
+if uploaded_files:
+    images = [Image.open(file) for file in uploaded_files]
+
+    st.header("Uploaded Images")
+    for i, image in enumerate(images):
+        st.image(image, caption=f"Image {i+1}", use_column_width=True)
+
+    # Transformation options
+    st.header("Select Transformations")
+    options = st.multiselect("Choose transformations:", [
+        "Rotation",
+        "Scaling",
+        "Shearing",
+        "Cropping",
+    ])
+
+    # Parameters for transformations
+    angle = scale_factor = shear_factor = left = top = right = bottom = None
+
+    if "Rotation" in options:
+        angle = st.slider("Rotation Angle (degrees):", 0, 360, 90)
+
+    if "Scaling" in options:
+        scale_factor = st.slider("Scaling Factor:", 0.1, 3.0, 1.0)
+
+    if "Shearing" in options:
+        shear_factor = st.slider("Shearing Factor:", -0.5, 0.5, 0.0)
+
+    if "Cropping" in options:
+        left = st.slider("Left Crop:", 0, min([image.width for image in images]) - 1, 0)
+        top = st.slider("Top Crop:", 0, min([image.height for image in images]) - 1, 0)
+        right = st.slider("Right Crop:", left + 1, min([image.width for image in images]), min([image.width for image in images]))
+        bottom = st.slider("Bottom Crop:", top + 1, min([image.height for image in images]), min([image.height for image in images]))
+
+    # Perform transformations
+    transformed_images = []
+
+    for image in images:
+        transformed_image = image.copy()
+
+        if "Rotation" in options and angle is not None:
+            transformed_image = transformed_image.rotate(angle)
+
+        if "Scaling" in options and scale_factor is not None:
+            new_size = (int(transformed_image.width * scale_factor), int(transformed_image.height * scale_factor))
+            transformed_image = transformed_image.resize(new_size)
+
+        if "Shearing" in options and shear_factor is not None:
+            matrix = [
+                1, shear_factor, 0,
+                0, 1, 0
+            ]
+            transformed_image = transformed_image.transform(transformed_image.size, Image.AFFINE, matrix)
+
+        if "Cropping" in options and left is not None and top is not None and right is not None and bottom is not None:
+            transformed_image = transformed_image.crop((left, top, right, bottom))
+
+        transformed_images.append(transformed_image)
+
+    # Display transformed images
+    st.header("Transformed Images")
+    for i, transformed_image in enumerate(transformed_images):
+        st.image(transformed_image, caption=f"Transformed Image {i+1}", use_column_width=True)
+
+    # Download all transformed images as a zip file
+    if transformed_images:
+        zip_buffer = io.BytesIO()
+        with zipfile.ZipFile(zip_buffer, "w") as zf:
+            for i, transformed_image in enumerate(transformed_images):
+                img_buffer = io.BytesIO()
+                transformed_image.save(img_buffer, format="PNG")
+                zf.writestr(f"transformed_image_{i+1}.png", img_buffer.getvalue())
+
+        zip_buffer.seek(0)
+        st.download_button(
+            label="Download All Transformed Images",
+            data=zip_buffer,
+            file_name="Transformed_images.zip",
+            mime="application/zip",
+        )