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import cv2 |
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import os |
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import base64 |
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import numpy as np |
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from PIL import ImageFont, ImageDraw, Image |
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import streamlit as st |
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from modules.Cartoon.main import cartoon |
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img_extensions = ["jpg","png","jpeg"] |
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def get_binary_file_downloader_html(bin_file,file_label='File'): |
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with open(bin_file,'rb') as f: |
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data = f.read() |
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bin_str = base64.b64encode(data).decode() |
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href = f'<h3><a href="data:application/octet-stream;base64,{bin_str}" download="{os.path.basename(bin_file)}">Download {file_label}</a></h3>' |
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return href |
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def image_transformations(result,filter,img_extension = "jpg"): |
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result = result[:,:,:3] |
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if filter == "Basic Image Editing": |
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gamma = st.slider("Gamma Correction",0.0,5.0,1.0,step = 0.1) |
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saturation = st.slider("Saturation", 0.0, 2.0, 1.0, step=0.1) |
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blurring = st.checkbox("Bluring", False) |
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if blurring: |
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col1,col2 = st.columns(2) |
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blur_area = col1.slider("Blur Area",1,100,1,2) |
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blur_intensity = col2.slider("Blur Intensity", 0, 500, 0, 1) |
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result = cv2.GaussianBlur(result, (blur_area, 1), blur_intensity) |
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apply_vignette = st.checkbox("Apply Vignette effect",False) |
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if apply_vignette: |
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vignette_effect = st.slider("Vignette Intensity",1,120,1) |
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rows, cols = result.shape[:2] |
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kernel_x = cv2.getGaussianKernel(cols, vignette_effect + 139) |
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kernel_y = cv2.getGaussianKernel(rows, vignette_effect + 139) |
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kernel = kernel_y*kernel_x.T |
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filter = 255 * kernel / np.linalg.norm(kernel) |
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vignette_img = np.copy(result) |
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for i in range(3): |
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vignette_img[:,:,i] = vignette_img[:,:,i]*filter |
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result = vignette_img |
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hsvImg = cv2.cvtColor(result, cv2.COLOR_BGR2HSV) |
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hsvImg[..., 1] = np.clip(hsvImg[..., 1] * saturation, 0, 255) |
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hsvImg[..., 2] = np.power((hsvImg[..., 2] / 255.0), 1 / (gamma + 0.1)) * 255.0 |
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result = cv2.cvtColor(hsvImg, cv2.COLOR_HSV2BGR) |
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elif filter == "Cartoonie": |
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line_size = st.slider("Number of edges",3,101,7,2) |
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blurVal = st.slider("Blurr effect",3,101,7,2) |
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totalCols = st.slider("Total Color in images",2,100,11,1) |
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result = cartoon(result,[line_size,blurVal,totalCols]) |
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if np.all(result != None): |
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st.image(result, use_column_width=True, clamp=True, channels="BGR") |
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filename = img_extension[0] + "." + img_extension[-1] |
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cv2.imwrite(filename, result) |
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st.markdown(get_binary_file_downloader_html(filename, |
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'From Here '), |
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unsafe_allow_html=True) |
