first commit

main.py

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+import streamlit as st
+import cv2
+import numpy as np
+from PIL import Image
+
+st.title("📸Image Processing App")
+
+# Upload image
+uploaded_file = st.file_uploader("Upload an Image", type=["png", "jpg", "jpeg"])
+
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+    
+    # Convert PIL image to OpenCV format
+    img_array = np.array(image)
+
+    # Show original image
+    st.subheader("Original vs Processed Image")
+    col1, col2 = st.columns(2)
+
+    with col1:
+        st.image(image, caption="Original Image", use_container_width=True)
+
+    processed_image = img_array  # Initialize processed_image with original image
+
+    # Convert to Grayscale
+    if st.button("Convert to Grayscale"):
+        processed_image = cv2.cvtColor(img_array, cv2.COLOR_RGB2GRAY)
+    
+    # Rotate Image
+    angle = st.slider("Select Rotation Angle", -180, 180, 0)
+    if st.button("Rotate Image"):
+        (h, w) = img_array.shape[:2]
+        center = (w // 2, h // 2)
+        matrix = cv2.getRotationMatrix2D(center, angle, 1.0)
+        processed_image = cv2.warpAffine(img_array, matrix, (w, h))
+    
+    # Add Text Overlay
+    text = st.text_input("Enter text to overlay on the image", "Hello")
+    if st.button("Apply Text Overlay"):
+        image_copy = img_array.copy()
+        font = cv2.FONT_HERSHEY_SIMPLEX
+        cv2.putText(image_copy, text, (50, 50), font, 1, (255, 0, 0), 2, cv2.LINE_AA)
+        processed_image = image_copy
+
+    # Show processed image in the second column
+    with col2:
+        st.image(processed_image, caption="Processed Image", use_container_width=True)

requirements.txt

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+ streamlit
+ cv2
+ numpy
+ PIL