second-commit

app.py

@@ -1,11 +1,49 @@
+import cv2
 import streamlit as st
-import pandas as pd
+import numpy as np
+from PIL import Image
 
-st.title('A Simple Streamlit Web App')
-name = st.text_input('Enter your name', '')
-st.write(f'Hello {name}!')
 
-x = st.slider('Select an integer x', 0, 10, 1)
-y = st.slider('Select an integer y', 0, 10, 1)
-df = pd.DataFrame({'x': [x], 'y': [y] , 'x + y': [x + y]}, index=['addition row'])
-st.write(df)
+def brighten_image(image, amount):
+    img_bright = cv2.convertScaleAbs(image, beta=amount)
+    return img_bright
+
+
+def blur_image(image, amount):
+    blur_img = cv2.GaussianBlur(image, (11, 11), amount)
+    return blur_img
+
+
+def enhance_details(img):
+    hdr = cv2.detailEnhance(img, sigma_s=12, sigma_r=0.15)
+    return hdr
+
+
+def main_loop():
+    st.title("OpenCV Demo App")
+    st.subheader("This app allows you to play with Image filters!")
+    st.text("We use OpenCV and Streamlit for this demo")
+
+    blur_rate = st.sidebar.slider("Blurring", min_value=0.5, max_value=3.5)
+    brightness_amount = st.sidebar.slider("Brightness", min_value=-50, max_value=50, value=0)
+    apply_enhancement_filter = st.sidebar.checkbox('Enhance Details')
+
+    image_file = st.file_uploader("Upload Your Image", type=['jpg', 'png', 'jpeg'])
+    if not image_file:
+        return None
+
+    original_image = Image.open(image_file)
+    original_image = np.array(original_image)
+
+    processed_image = blur_image(original_image, blur_rate)
+    processed_image = brighten_image(processed_image, brightness_amount)
+
+    if apply_enhancement_filter:
+        processed_image = enhance_details(processed_image)
+
+    st.text("Original Image vs Processed Image")
+    st.image([original_image, processed_image])
+
+
+if __name__ == '__main__':
+    main_loop()

requirements.txt

@@ -1 +1,3 @@
-streamlit==1.10.0
+streamlit==1.10.0
+opencv-python==4.6.0.66
+Pillow==9.1.1