Assignment_App.py

import streamlit as st
import cv2
import numpy as np
from PIL import Image

st.set_page_config(page_title="OpenCV Playground", layout="wide")

st.title("🧠 OpenCV Learning Playground")
st.markdown("### Learn and Interact with OpenCV through a Visual Interface")

with st.expander("ℹ️ Instructions & Info"):
    st.markdown("""
    This app helps you **interactively explore OpenCV** through two main categories:
    
    **1. Image Manipulation & Transformation**
    - Resize / Scale
    - Crop
    - Rotate
    - Flip (Vertical / Horizontal / Both)

    **2. Drawing on Images**
    - Draw Line
    - Draw Rectangle
    - Draw Circle
    - Add Text

    After performing any operation, you can **preview the result** and download the modified image.
    """)

uploaded_file = st.sidebar.file_uploader(
    "📁 Upload an image", type=["jpg", "jpeg", "png"]
)

if uploaded_file:
    file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
    img = cv2.imdecode(file_bytes, 1)
    img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    h, w = img.shape[:2]

    choice = st.sidebar.radio(
        "Choose Operation Category",
        ["Image Manipulation & Transformation", "Basic Drawing Techniques"],
    )

    def select_position(section, img_shape, size=(100, 100)):
        h, w = img_shape[:2]
        sw, sh = size
        positions = {
            "center": ((w - sw) // 2, (h - sh) // 2),
            "left": (0, (h - sh) // 2),
            "right": (w - sw, (h - sh) // 2),
            "top left": (0, 0),
            "top right": (w - sw, 0),
            "bottom left": (0, h - sh),
            "bottom right": (w - sw, h - sh),
        }
        if section in positions:
            return positions[section]
        else:
            x = st.sidebar.number_input("Custom X", 0, w, 0)
            y = st.sidebar.number_input("Custom Y", 0, h, 0)
            return (x, y)

    result = img.copy()

    if choice == "Image Manipulation & Transformation":
        transform_option = st.sidebar.selectbox(
            "Choose Transformation", ["Resize", "Crop", "Rotate", "Flip"]
        )

        if transform_option == "Resize":
            scale = st.sidebar.slider("Scale factor", 0.1, 3.0, 1.0, 0.1)
            result = cv2.resize(img, (int(w * scale), int(h * scale)))

        elif transform_option == "Crop":
            section = st.sidebar.selectbox(
                "Select Crop Section",
                [
                    "center",
                    "left",
                    "top left",
                    "bottom left",
                    "right",
                    "top right",
                    "bottom right",
                    "custom",
                ],
            )
            crop_w = st.sidebar.slider("Crop Width", 10, w, 100)
            crop_h = st.sidebar.slider("Crop Height", 10, h, 100)
            x, y = select_position(section, img.shape, size=(crop_w, crop_h))
            x, y = int(x), int(y)
            result = img[y : y + crop_h, x : x + crop_w]

        elif transform_option == "Rotate":
            angle = st.sidebar.slider("Rotation Angle", -180, 180, 0)
            center = (w // 2, h // 2)
            M = cv2.getRotationMatrix2D(center, angle, 1.0)
            result = cv2.warpAffine(img, M, (w, h))

        elif transform_option == "Flip":
            direction = st.sidebar.selectbox(
                "Flip Direction", ["vertical", "horizontal", "both"]
            )
            flip_code = {"vertical": 0, "horizontal": 1, "both": -1}
            result = cv2.flip(img, flip_code[direction])

    elif choice == "Basic Drawing Techniques":
        draw_option = st.sidebar.selectbox(
            "Choose Drawing Type", ["Line", "Rectangle", "Circle", "Text"]
        )

        if draw_option in ["Line", "Rectangle", "Circle", "Text"]:
            section = st.sidebar.selectbox(
                "Select Position",
                [
                    "center",
                    "left",
                    "top left",
                    "bottom left",
                    "right",
                    "top right",
                    "bottom right",
                    "custom",
                ],
            )

        if draw_option == "Line":
            x, y = select_position(section, img.shape)
            result = cv2.line(
                img.copy(), (int(x), int(y)), (int(x) + 100, int(y)), (255, 255, 255), 5
            )

        elif draw_option == "Rectangle":
            rect_w = 100
            rect_h = 100
            x, y = select_position(section, img.shape, size=(rect_w, rect_h))
            result = cv2.rectangle(
                img.copy(),
                (int(x), int(y)),
                (int(x) + rect_w, int(y) + rect_h),
                (255, 0, 0),
                5,
            )

        elif draw_option == "Circle":
            radius = 50
            x, y = select_position(section, img.shape, size=(radius * 2, radius * 2))
            result = cv2.circle(
                img.copy(), (int(x) + radius, int(y) + radius), radius, (0, 255, 0), 5
            )

        elif draw_option == "Text":
            user_text = st.sidebar.text_input("Enter Text", "Hello OpenCV")
            font = cv2.FONT_HERSHEY_SIMPLEX
            font_scale = 2
            thickness = 3
            (text_w, text_h), _ = cv2.getTextSize(
                user_text, font, font_scale, thickness
            )
            x, y = select_position(section, img.shape, size=(text_w, text_h))
            y += text_h
            result = cv2.putText(
                img.copy(),
                user_text,
                (int(x), int(y)),
                font,
                font_scale,
                (0, 255, 255),
                thickness,
            )

    if result is not None:
        st.subheader("📸 Comparison: Original vs Modified")
        col1, col2 = st.columns(2)
        with col1:
            st.image(img_rgb, caption="Original", use_container_width=True)
        with col2:
            st.image(
                cv2.cvtColor(result, cv2.COLOR_BGR2RGB),
                caption="Modified",
                use_container_width=True,
            )

        st.download_button(
            label="📥 Download Modified Image",
            data=cv2.imencode(".jpg", result)[1].tobytes(),
            file_name="processed_image.jpg",
            mime="image/jpeg",
        )
else:
    st.info("Please upload an image to begin.")