initial commit

app.py

@@ -0,0 +1,101 @@
+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.")

requirements.txt

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+streamlit
+opencv-python
+numpy
+pillow