Update 8_Image_Augumentation.py

8_Image_Augumentation.py

@@ -1,92 +0,0 @@
-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",
-        )