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| # import streamlit as st | |
| # import cv2 | |
| # import numpy as np | |
| # from PIL import Image | |
| # # Title with emojis | |
| # st.title("🖼️ Image Processing\n(🔍 Comparison View)") | |
| # # Sidebar for image upload and operation selection with emojis | |
| # with st.sidebar: | |
| # st.write("📤 Upload & Select") | |
| # uploaded_file = st.file_uploader("🌄 Upload an Image", type=["png", "jpg", "jpeg"]) | |
| # option = st.selectbox("🛠️ Choose a comparison:", [ | |
| # "🚫 None", "⚫ Convert to Grayscale", "🔄 Rotate Image", "🌫️ Blur Image", | |
| # "🌠 Convert to Color Space", "✂️ Edge Detection" | |
| # ]) | |
| # # Function to process the image | |
| # def process_image(image, operation, value=None, extra_value=None): | |
| # if operation == "🚫 None": | |
| # return image | |
| # elif operation == "🔲 Convert to Grayscale": | |
| # return cv2.cvtColor(image, cv2.COLOR_RGB2GRAY) | |
| # elif operation == "🔄 Rotate Image": | |
| # if value is not None: | |
| # (h, w) = image.shape[:2] | |
| # center = (w // 2, h // 2) | |
| # matrix = cv2.getRotationMatrix2D(center, value, 1.0) | |
| # return cv2.warpAffine(image, matrix, (w, h)) | |
| # elif operation == "🌫️ Blur Image": | |
| # if value is not None: | |
| # kernel_size = (value * 2 + 1, value * 2 + 1) # Ensure odd kernel size | |
| # return cv2.GaussianBlur(image, kernel_size, 0) | |
| # elif operation == "🌠 Convert to Color Space": | |
| # if value == "RGB": | |
| # return image # Already in RGB | |
| # elif value == "BGR2RGB": | |
| # return cv2.cvtColor(image, cv2.COLOR_RGB2BGR) # Corrected to RGB2BGR | |
| # elif value == "Grayscale": | |
| # return cv2.cvtColor(image, cv2.COLOR_RGB2GRAY) | |
| # elif operation == "✂️ Edge Detection": | |
| # if value is not None and extra_value is not None: | |
| # gray_image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY) | |
| # return cv2.Canny(gray_image, value, extra_value) | |
| # return image | |
| # if uploaded_file is not None: | |
| # # Read image | |
| # image = Image.open(uploaded_file) | |
| # img_array = np.array(image) | |
| # processed_img = img_array.copy() | |
| # # Operation-specific controls in the main area with emojis | |
| # if option == "🔄 Rotate Image": | |
| # angle = st.slider("↪️ Select Rotation Angle", -180, 180, 0) | |
| # processed_img = process_image(img_array, option, angle) | |
| # elif option == "🌫️ Blur Image": | |
| # blur_level = st.slider("🎨 Select Blur Level", 1, 20, 5) | |
| # processed_img = process_image(img_array, option, blur_level) | |
| # elif option == "🌠 Convert to Color Space": | |
| # color_space = st.selectbox("🎨 Choose a color space:", ["RGB", "BGR2RGB", "Grayscale"]) | |
| # processed_img = process_image(img_array, option, color_space) | |
| # elif option == "✂️ Edge Detection": | |
| # low_threshold = st.slider("🔽 Lower Threshold", 0, 255, 50) | |
| # high_threshold = st.slider("🔼 Upper Threshold", 0, 255, 150) | |
| # processed_img = process_image(img_array, option, low_threshold, high_threshold) | |
| # else: | |
| # processed_img = process_image(img_array, option) | |
| # # Display images side by side with emojis in captions | |
| # col1, col2 = st.columns(2) | |
| # with col1: | |
| # st.image(image, caption="🌟 Original Image", use_container_width=True) | |
| # with col2: | |
| # # Convert processed image to appropriate format for display | |
| # if len(processed_img.shape) == 2: # Grayscale image | |
| # processed_img_rgb = cv2.cvtColor(processed_img, cv2.COLOR_GRAY2RGB) | |
| # else: | |
| # processed_img_rgb = processed_img # Already in RGB | |
| # # Dynamic caption with emojis based on operation | |
| # if option == "🚫 None": | |
| # caption = "🚫 No Processing Applied" | |
| # elif option == "🔲 Convert to Grayscale": | |
| # caption = "🔲 Grayscale Image" | |
| # elif option == "🔄 Rotate Image": | |
| # caption = f"🔄 Rotated by {angle}°" | |
| # elif option == "🌫️ Blur Image": | |
| # caption = f"🌫️ Blurred (Level {blur_level})" | |
| # elif option == "🌠 Convert to Color Space": | |
| # caption = f"🌠 {color_space} Image" | |
| # elif option == "✂️ Edge Detection": | |
| # caption = "✂️ Edge Detection (Canny)" | |
| # st.image(processed_img_rgb, caption=caption, use_container_width=True) | |
| # # Download button with emoji | |
| # if len(processed_img.shape) == 2: | |
| # processed_img_download = cv2.cvtColor(processed_img, cv2.COLOR_GRAY2BGR) | |
| # else: | |
| # processed_img_download = cv2.cvtColor(processed_img, cv2.COLOR_RGB2BGR) | |
| # is_success, buffer = cv2.imencode(".png", processed_img_download) | |
| # if is_success: | |
| # st.download_button( | |
| # label="💾 Download Processed Image", | |
| # data=buffer.tobytes(), | |
| # file_name="processed_image.png", | |
| # mime="image/png" | |
| # ) | |
| import streamlit as st | |
| import cv2 | |
| import numpy as np | |
| from PIL import Image | |
| # Title with emojis | |
| st.title("🖼️ Image Processing\n(🔍 Comparison View)") | |
| # Sidebar for image upload and operation selection with emojis | |
| with st.sidebar: | |
| st.write("📤 Upload & Select") | |
| uploaded_file = st.file_uploader("🌄 Upload an Image", type=["png", "jpg", "jpeg"]) | |
| option = st.selectbox("🛠️ Choose a comparison:", [ | |
| "🚫 None", "🔲 Convert to Grayscale", "🔄 Rotate Image", "🌫️ Blur Image", | |
| "🌠 Convert to Color Space", "✂️ Edge Detection" | |
| ]) | |
| # Function to process the image | |
| def process_image(image, operation, value=None, extra_value=None): | |
| if operation == "🚫 None": | |
| return image | |
| elif operation == "🔲 Convert to Grayscale": | |
| return cv2.cvtColor(image, cv2.COLOR_RGB2GRAY) | |
| elif operation == "🔄 Rotate Image": | |
| if value is not None: | |
| (h, w) = image.shape[:2] | |
| center = (w // 2, h // 2) | |
| matrix = cv2.getRotationMatrix2D(center, value, 1.0) | |
| return cv2.warpAffine(image, matrix, (w, h)) | |
| elif operation == "🌫️ Blur Image": | |
| if value is not None: | |
| kernel_size = (value * 2 + 1, value * 2 + 1) # Ensure odd kernel size | |
| return cv2.GaussianBlur(image, kernel_size, 0) | |
| elif operation == "🌠 Convert to Color Space": | |
| if value == "RGB": | |
| return image # Already in RGB | |
| elif value == "BGR2RGB": | |
| return cv2.cvtColor(image, cv2.COLOR_RGB2BGR) | |
| elif value == "Grayscale": | |
| return cv2.cvtColor(image, cv2.COLOR_RGB2GRAY) | |
| elif operation == "✂️ Edge Detection": | |
| if value is not None and extra_value is not None: | |
| gray_image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY) | |
| return cv2.Canny(gray_image, value, extra_value) | |
| return image | |
| if uploaded_file is not None: | |
| # Read image | |
| image = Image.open(uploaded_file) | |
| img_array = np.array(image) | |
| processed_img = img_array.copy() | |
| # Operation-specific controls in the main area with emojis | |
| if option == "🔄 Rotate Image": | |
| angle = st.slider("↪️ Select Rotation Angle", -180, 180, 0) | |
| processed_img = process_image(img_array, option, angle) | |
| elif option == "🌫️ Blur Image": | |
| blur_level = st.slider("🎨 Select Blur Level", 1, 20, 5) | |
| processed_img = process_image(img_array, option, blur_level) | |
| elif option == "🌠 Convert to Color Space": | |
| color_space = st.selectbox("🎨 Choose a color space:", ["RGB", "BGR2RGB", "Grayscale"]) | |
| processed_img = process_image(img_array, option, color_space) | |
| elif option == "✂️ Edge Detection": | |
| low_threshold = st.slider("🔽 Lower Threshold", 0, 255, 50) | |
| high_threshold = st.slider("🔼 Upper Threshold", 0, 255, 150) | |
| processed_img = process_image(img_array, option, low_threshold, high_threshold) | |
| else: | |
| processed_img = process_image(img_array, option) | |
| # Display images side by side with emojis in captions | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| st.image(image, caption="🌟 Original Image", use_container_width=True) | |
| with col2: | |
| # Convert processed image to appropriate format for display | |
| if len(processed_img.shape) == 2: # Grayscale image | |
| processed_img_rgb = cv2.cvtColor(processed_img, cv2.COLOR_GRAY2RGB) | |
| else: | |
| processed_img_rgb = processed_img # Already in RGB | |
| # Dynamic caption with emojis based on operation | |
| caption = "🚫 No Processing Applied" # Default caption | |
| if option == "🚫 None": | |
| caption = "🚫 No Processing Applied" | |
| elif option == "🔲 Convert to Grayscale": | |
| caption = "🔲 Grayscale Image" | |
| elif option == "🔄 Rotate Image": | |
| caption = f"🔄 Rotated by {angle}°" | |
| elif option == "🌫️ Blur Image": | |
| caption = f"🌫️ Blurred (Level {blur_level})" | |
| elif option == "🌠 Convert to Color Space": | |
| caption = f"🌠 {color_space} Image" | |
| elif option == "✂️ Edge Detection": | |
| caption = "✂️ Edge Detection (Canny)" | |
| st.image(processed_img_rgb, caption=caption, use_container_width=True) | |
| # Download button with emoji | |
| if len(processed_img.shape) == 2: | |
| processed_img_download = cv2.cvtColor(processed_img, cv2.COLOR_GRAY2BGR) | |
| else: | |
| processed_img_download = cv2.cvtColor(processed_img, cv2.COLOR_RGB2BGR) | |
| is_success, buffer = cv2.imencode(".png", processed_img_download) | |
| if is_success: | |
| st.download_button( | |
| label="💾 Download Processed Image", | |
| data=buffer.tobytes(), | |
| file_name="processed_image.png", | |
| mime="image/png" | |
| ) |