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| import streamlit as st | |
| import cv2 | |
| import numpy as np | |
| from PIL import Image | |
| st.title("OpenCV Image Processing") | |
| st.write("This is a simple web app to demonstrate how to use OpenCV with Streamlit.") | |
| uploaded_file = st.file_uploader( | |
| "Choose an image...", type=["png", "jpg", "jpeg"]) | |
| if uploaded_file is not None: | |
| st.text("Image uploaded successfully.") | |
| st.write("Please select an option from the checkboxes below:") | |
| options = { | |
| "Show Grayscale": False, | |
| "Resize Image": False, | |
| "Crop Image": False, | |
| "Rotate Image": False, | |
| "Flip Image": False, | |
| } | |
| for option_name in options: | |
| options[option_name] = st.checkbox(option_name) | |
| st.subheader("Original vs Processed Image") | |
| col1, col2 = st.columns(2) | |
| if uploaded_file is not None: # Check if a file was actually uploaded | |
| image = Image.open(uploaded_file).convert( | |
| "RGB") # CRUCIAL: Convert to RGB immediately | |
| original_image = np.array(image) | |
| processed_image = original_image.copy() | |
| with col1: | |
| st.image(original_image, caption="Original Image", | |
| channels="RGB") # Display in RGB | |
| if any(options.values()): | |
| if options["Show Grayscale"]: | |
| processed_image = cv2.cvtColor( | |
| processed_image, cv2.COLOR_RGB2GRAY) | |
| if options["Resize Image"]: | |
| width = st.slider( | |
| "New Width", 100, original_image.shape[1] * 2, original_image.shape[1], step=10) | |
| height = st.slider( | |
| "New Height", 100, original_image.shape[0] * 2, original_image.shape[0], step=10) | |
| processed_image = cv2.resize(processed_image, (width, height)) | |
| if len(processed_image.shape) == 2: | |
| processed_image = cv2.cvtColor( | |
| processed_image, cv2.COLOR_GRAY2RGB) | |
| if options["Crop Image"]: | |
| x1 = st.slider("X1", 0, original_image.shape[1], 0) | |
| y1 = st.slider("Y1", 0, original_image.shape[0], 0) | |
| x2 = st.slider( | |
| "X2", 0, original_image.shape[1], original_image.shape[1]) | |
| y2 = st.slider( | |
| "Y2", 0, original_image.shape[0], original_image.shape[0]) | |
| processed_image = processed_image[y1:y2, x1:x2] | |
| if len(processed_image.shape) == 2: | |
| processed_image = cv2.cvtColor( | |
| processed_image, cv2.COLOR_GRAY2RGB) | |
| if options["Rotate Image"]: | |
| angle = st.slider("Rotation Angle", -180, 180, 0) | |
| rows, cols = processed_image.shape[:2] | |
| M = cv2.getRotationMatrix2D((cols / 2, rows / 2), angle, 1) | |
| processed_image = cv2.warpAffine( | |
| processed_image, M, (cols, rows)) | |
| if len(processed_image.shape) == 2: | |
| processed_image = cv2.cvtColor( | |
| processed_image, cv2.COLOR_GRAY2RGB) | |
| if options["Flip Image"]: | |
| flip_mode = st.selectbox( | |
| "Flip Mode", [("Vertical", 0), ("Horizontal", 1), ("Both", -1)]) | |
| processed_image = cv2.flip(processed_image, flip_mode[1]) | |
| if len(processed_image.shape) == 2: | |
| processed_image = cv2.cvtColor( | |
| processed_image, cv2.COLOR_GRAY2RGB) | |
| with col2: | |
| if len(processed_image.shape) == 3: | |
| processed_channels = "RGB" # Display in RGB | |
| elif len(processed_image.shape) == 2: | |
| processed_channels = "GRAY" | |
| else: | |
| processed_channels = None | |
| if processed_channels: | |
| st.image(processed_image, caption="Processed Image", | |
| channels=processed_channels) | |
| else: | |
| st.write("Unexpected image format after processing.") | |
| else: | |
| with col2: | |
| st.write("No processing applied yet.") | |