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Browse files- app.py +236 -0
- packages.txt +2 -0
- requirements.txt +5 -0
app.py
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| 1 |
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# app.py
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| 2 |
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import streamlit as st
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import cv2
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import numpy as np
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from PIL import Image
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from io import BytesIO
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import mediapipe as mp # NEW for background removal
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# ----- Custom CSS Styling -----
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def local_css():
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st.markdown("""
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<style>
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/* Main Background */
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.stApp {
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background-image: url('https://img.freepik.com/free-photo/arrows-pastel-colors_23-2148488400.jpg?semt=ais_hybrid&w=740');
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background-size: cover;
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background-position: center;
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background-attachment: fixed;
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min-height: 100vh;
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color: darkred;
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}
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/* Sidebar Background */
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section[data-testid="stSidebar"] {
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background-image: url('https://i.pinimg.com/736x/10/76/df/1076df6744238e75e79047f7c2d2bbec.jpg');
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background-size: cover;
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background-position: center;
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}
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/* Container Styling */
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.css-1d391kg {
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background: linear-gradient(135deg, #89f7fe 0%, #66a6ff 100%);
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border-radius: 15px;
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padding: 20px;
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}
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/* Button Styling */
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.stButton > button {
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color: white;
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background: linear-gradient(45deg, #ff6a00, #ee0979);
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border: none;
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border-radius: 10px;
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padding: 0.75em 1.5em;
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font-size: 1.1em;
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box-shadow: 0px 4px 15px rgba(0,0,0,0.2);
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}
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.stButton > button:hover {
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background: linear-gradient(45deg, #43cea2, #185a9d);
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}
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/* Profile Links Styling */
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.profile-links img {
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vertical-align: middle;
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margin-right: 8px;
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}
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.profile-links a {
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text-decoration: none;
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color: #333;
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font-size: 0.9em;
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}
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</style>
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""", unsafe_allow_html=True)
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def sidebar_profiles():
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st.sidebar.markdown("### 🎉Author: Maria Nadeem🌟")
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st.sidebar.markdown("### 🔗 Connect With Me")
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st.sidebar.markdown("""
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<hr>
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<div class="profile-links">
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<a href="https://github.com/marianadeem755" target="_blank">
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<img src="https://cdn-icons-png.flaticon.com/512/25/25231.png" width="20px"> GitHub
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</a><br><br>
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<a href="https://www.kaggle.com/marianadeem755" target="_blank">
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<img src="https://cdn4.iconfinder.com/data/icons/logos-and-brands/512/189_Kaggle_logo_logos-512.png" width="20px"> Kaggle
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</a><br><br>
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<a href="mailto:marianadeem755@gmail.com">
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<img src="https://cdn-icons-png.flaticon.com/512/561/561127.png" width="20px"> Email
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</a><br><br>
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<a href="https://huggingface.co/maria355" target="_blank">
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<img src="https://huggingface.co/front/assets/huggingface_logo-noborder.svg" width="20px"> Hugging Face
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</a>
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</div>
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<hr>
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""", unsafe_allow_html=True)
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# ----- Filters Functions -----
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def apply_grayscale(img):
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return cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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def apply_blur(img, ksize):
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return cv2.GaussianBlur(img, (ksize, ksize), 0)
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def apply_canny(img, threshold1, threshold2):
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return cv2.Canny(img, threshold1, threshold2)
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def apply_sepia(img):
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kernel = np.array([[0.272, 0.534, 0.131],
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[0.349, 0.686, 0.168],
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[0.393, 0.769, 0.189]])
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sepia_img = cv2.transform(img, kernel)
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sepia_img = np.clip(sepia_img, 0, 255)
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return sepia_img
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def apply_pencil_sketch(img):
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if len(img.shape) == 3:
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gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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else:
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gray_img = img
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inv_img = 255 - gray_img
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blur_img = cv2.GaussianBlur(inv_img, (21, 21), 0)
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sketch = cv2.divide(gray_img, 255 - blur_img, scale=256)
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return sketch
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def apply_invert(img):
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return cv2.bitwise_not(img)
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def apply_background_removal(img):
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mp_selfie_segmentation = mp.solutions.selfie_segmentation
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with mp_selfie_segmentation.SelfieSegmentation(model_selection=1) as selfie_segmentation:
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rgb_img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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results = selfie_segmentation.process(rgb_img)
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mask = results.segmentation_mask
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condition = mask > 0.5
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bg_color = np.ones(img.shape, dtype=np.uint8) * 255
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output_img = np.where(condition[..., None], img, bg_color)
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return output_img
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# Convert to PIL
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def convert_image(img):
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if len(img.shape) == 2:
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return Image.fromarray(img)
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else:
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return Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
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# Downloadable image
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def download_image(img):
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buf = BytesIO()
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img.save(buf, format="PNG")
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byte_im = buf.getvalue()
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return byte_im
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# ----- Streamlit App Starts Here -----
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def main():
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st.set_page_config(page_title="Advanced Image Filter Studio", page_icon="🎨", layout="wide")
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local_css()
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st.title("🎨 Advanced Image Filter Studio")
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st.write("Upload an image, apply **amazing filters**, and download your creation!")
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# Sidebar Profiles
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sidebar_profiles()
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# Sidebar
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st.sidebar.header("1. Upload Image")
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uploaded_file = st.sidebar.file_uploader("Choose an image", type=["jpg", "jpeg", "png"])
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if uploaded_file is not None:
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file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
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opencv_image = cv2.imdecode(file_bytes, 1)
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# Filters Section
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st.sidebar.header("2. Choose Filters")
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grayscale = st.sidebar.checkbox("Grayscale")
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blur = st.sidebar.checkbox("Blur")
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canny = st.sidebar.checkbox("Edge Detection")
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sepia = st.sidebar.checkbox("Sepia Effect")
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sketch = st.sidebar.checkbox("Pencil Sketch")
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invert = st.sidebar.checkbox("Invert Colors")
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remove_bg = st.sidebar.checkbox("Remove Background (Simple)")
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st.sidebar.header("3. Filter Parameters")
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blur_strength = st.sidebar.slider("Blur Intensity (odd numbers)", 1, 49, 15, step=2)
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threshold1 = st.sidebar.slider("Canny Threshold1", 50, 300, 100)
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threshold2 = st.sidebar.slider("Canny Threshold2", 50, 300, 150)
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# Process Image
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final_image = opencv_image.copy()
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with st.spinner("🖌️ Applying Filters..."):
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if grayscale:
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final_image = apply_grayscale(final_image)
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if blur:
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if len(final_image.shape) == 2:
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final_image = cv2.cvtColor(final_image, cv2.COLOR_GRAY2BGR)
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final_image = apply_blur(final_image, blur_strength)
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if canny:
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if len(final_image.shape) != 2:
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final_image = cv2.cvtColor(final_image, cv2.COLOR_BGR2GRAY)
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final_image = apply_canny(final_image, threshold1, threshold2)
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if sepia:
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if len(final_image.shape) == 2:
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final_image = cv2.cvtColor(final_image, cv2.COLOR_GRAY2BGR)
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final_image = apply_sepia(final_image)
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if sketch:
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if len(final_image.shape) != 2:
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final_image = cv2.cvtColor(final_image, cv2.COLOR_BGR2GRAY)
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final_image = apply_pencil_sketch(final_image)
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if invert:
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final_image = apply_invert(final_image)
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if remove_bg:
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if len(final_image.shape) != 3 or final_image.shape[2] != 3:
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final_image = cv2.cvtColor(final_image, cv2.COLOR_GRAY2BGR)
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final_image = apply_background_removal(final_image)
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# Columns to show images
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col1, col2 = st.columns(2)
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with col1:
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st.subheader("Original Image")
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st.image(uploaded_file, use_column_width=True)
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with col2:
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st.subheader("Processed Image")
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final_pil = convert_image(final_image)
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st.image(final_pil, use_column_width=True)
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# Download button
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st.markdown("---")
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st.download_button(
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label="📥 Download Processed Image",
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data=download_image(final_pil),
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file_name="processed_image.png",
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mime="image/png"
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)
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else:
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st.info("👈 Please upload an image from the sidebar to get started.")
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if __name__ == "__main__":
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main()
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packages.txt
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libgl1
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libglib2.0-0
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requirements.txt
ADDED
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@@ -0,0 +1,5 @@
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streamlit
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opencv-python
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Pillow
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numpy
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mediapipe
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