Initial Commit

app.py

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+import os,cv2
+import numpy as np
+import streamlit as st
+from webcam import webcam
+from images import image_transformations
+
+title = st.empty()
+title.header("Image Filter")
+img_extensions = ["jpg","png","jpeg"]
+
+def show_info():
+    st.subheader('''
+    Creator Jainam Jain: 
+    ''')
+    st.markdown("### **Filters used:Cartoon")
+    st.write("")
+st.sidebar.subheader("Choose the mode of operation: ")
+selected_option = st.sidebar.selectbox("",["Select from below","Image Filters","Video Filters"])
+
+if selected_option == "Image Filters":
+    title.header("Image Filters")
+    img_operation_mode = st.selectbox("Upload Images from: ",["--  Select from below  --","Local Storage","Take a snap from Webcam"])
+
+    if img_operation_mode == "Local Storage":
+        uploaded_file = st.file_uploader("Upload images from local storage here",type = img_extensions)
+        if uploaded_file is not None:
+            img_bytes = uploaded_file.read()
+            decoded_img = cv2.imdecode(np.frombuffer(img_bytes, np.uint8), -1)
+            result = decoded_img
+
+            filter = st.selectbox("Choose an Image filter: ",["Basic Image Editing","Thug Life","Green Screen","Moustaches",\
+            "Devil-ie","Heart Eyes","John Cena XD","Cartoonie","Face Blur"],0)
+            image_transformations(result,filter,uploaded_file.name.split("."))
+
+    elif img_operation_mode == "Take a snap from Webcam":
+        result = webcam()
+        if result is None:
+            st.write("Waiting for capture...")
+        else:
+            st.write("Got an image from the webcam :P")
+            result = cv2.cvtColor(np.asarray(result,np.uint8),cv2.COLOR_RGB2BGR)
+
+            filter = st.selectbox("Choose an Image filter: ",["Basic Image Editing","Thug Life","Green Screen","Moustaches",\
+            "Devil-ie","Heart Eyes","John Cena XD","Cartoonie","Face Blur"],0)
+            image_transformations(result,filter)
+
+    else:
+        st.sidebar.markdown('''
+        This section contains filters to be applied on images.
+
+        Images can be uploaded either from local storage (or) from your webcamera.
+        ''')
+        st.sidebar.markdown("Choose the source of image, from the drop list on right :point_right:")
+        st.sidebar.subheader("Tips for operating on Image Filters: ")
+        st.sidebar.markdown('''
+            * Un edited pictures provide the best results.
+            * Link to download the edited pictures are at the bottom of the page
+            ''')
+

images.py

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

modules/Blurr/main.py

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+import cv2
+import numpy as np
+from helper.utils import points2array
+
+def blur_all_faces(input_imag,landmark_files):
+    detector,predictor = landmark_files
+    msg = None
+    detections = detector(input_imag, 1)
+    if len(detections) == 0:
+        msg = "No faces detected"
+        return input_imag, msg
+    
+    canvas = input_imag.copy()
+    for rect in detections:
+        landmarks = predictor(input_imag, rect)
+        landmarks = points2array(landmarks.parts())
+        indices = list(range(16)) + [26,25,24,19,18,17,0]
+        pts = np.array(landmarks)[indices].reshape(-1,1,2)        
+        canvas = cv2.fillPoly(canvas,[pts],(255,255,255))
+        canvas = cv2.cvtColor(canvas,cv2.COLOR_BGR2GRAY)
+        face_mask = cv2.threshold(canvas, 250, 255, cv2.THRESH_BINARY)[1]
+        face_mask_in = cv2.bitwise_not(face_mask)
+        blurred_face = cv2.GaussianBlur(input_imag, (37, 37), 150)
+        blurred_face = cv2.bitwise_and(blurred_face, blurred_face, mask=face_mask_inv)
+        bg = cv2.bitwise_and(input_imag, input_imag, mask=face_mask_in)
+        input_img = cv2.bitwise_or(bg,blurred_face)
+
+        return input_img,msg
+    
+
+

modules/Cartoon/main.py

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+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+
+def edge_mask(img, line_size=7, blur_value=7):
+    gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
+    gray_blur = cv2.medianBlur(gray, blur_value)
+    edges = cv2.adaptiveThreshold(gray_blur, 255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,line_size, blur_value)
+    return edges
+
+def color_quantization(img,k):
+    data = np.float32(img).reshape((-1,3))
+    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER,20,0.001)
+    ret, label, center = cv2.kmeans(data, k, None, criteria, 10, cv2.KMEANS_RANDOM_CENTERS)
+    center = np.uint8(center)
+    result = center[label.flatten()]
+    result = result.reshape(img.shape)
+    return result
+def cartoon(img,params=[7,7,11]):
+
+    edges = edge_mask(img, params[0], params[1])
+    res = color_quantization(img,params[2])
+    blurr = cv2.bilateralFilter(res, d=7, sigmaColor=200,sigmaSpace=200)
+    c = cv2.bitwise_and(blurr,blurr,mask=edges)
+    return c

requiremments.txt

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+altair==5.2.0
+attrs==23.2.0
+blinker==1.7.0
+cachetools==5.3.2
+certifi==2023.11.17
+charset-normalizer==3.3.2
+click==8.1.7
+colorama==0.4.6
+contourpy==1.2.0
+cycler==0.12.1
+fonttools==4.47.0
+gitdb==4.0.11
+GitPython==3.1.40
+helper==2.5.0
+helper-utils==0.0.8
+idna==3.6
+importlib-metadata==6.11.0
+imutils==0.5.4
+Jinja2==3.1.2
+jsonschema==4.20.0
+jsonschema-specifications==2023.12.1
+kiwisolver==1.4.5
+markdown-it-py==3.0.0
+MarkupSafe==2.1.3
+matplotlib==3.8.2
+mdurl==0.1.2
+numpy==1.26.3
+opencv-python==4.9.0.80
+packaging==23.2
+pandas==2.1.4
+peppercorn==0.6
+pillow==10.2.0
+protobuf==4.25.1
+pyarrow==14.0.2
+pydeck==0.8.1b0
+Pygments==2.17.2
+pyparsing==3.1.1
+python-dateutil==2.8.2
+python-helper-utils==0.1.1
+pytz==2023.3.post1
+PyYAML==6.0.1
+referencing==0.32.1
+requests==2.31.0
+rich==13.7.0
+rpds-py==0.16.2
+six==1.16.0
+smmap==5.0.1
+streamlit==1.29.0
+tenacity==8.2.3
+toml==0.10.2
+toolz==0.12.0
+tornado==6.4
+typing_extensions==4.9.0
+tzdata==2023.4
+tzlocal==5.2
+urllib3==2.1.0
+utils==1.0.2
+validators==0.22.0
+watchdog==3.0.0
+webcam==1.34
+zipp==3.17.0