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Code.py

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+# %%
+import cv2
+import numpy as np
+from streamlit_webrtc import VideoTransformerBase, webrtc_streamer
+
+# %%
+glasses=cv2.imread('Train/glasses.png',cv2.IMREAD_UNCHANGED)
+mustache=cv2.imread('Train/mustache.png',cv2.IMREAD_UNCHANGED)
+
+# %%
+glassesCasc=cv2.CascadeClassifier('Train/third-party/frontalEyes35x16.xml')
+noseCasc=cv2.CascadeClassifier('Train/third-party/Nose18x15.xml')
+
+def apply_effects(frame):
+    gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
+    eyes = glassesCasc.detectMultiScale(gray, 1.5, 5, 0)
+    for (x, y, w, h) in eyes:
+        glasses_resized = cv2.resize(glasses, (w, h))
+        alpha_channel = glasses_resized[:, :, 3] / 255.0
+        
+        # Create a mask for the glasses
+        glasses_mask = np.zeros_like(glasses_resized[:, :, 3])
+        
+        # Copy alpha channel to mask and apply threshold
+        glasses_mask[glasses_resized[:, :, 3] > 0] = 255
+        
+        # Overlay the glasses using the mask
+        for c in range(0, 3):
+            frame[y:y+h, x:x+w, c] = (1 - alpha_channel) * frame[y:y+h, x:x+w, c] + alpha_channel * glasses_resized[:, :, c]
+
+    nose=noseCasc.detectMultiScale(gray,1.3,5,0)
+    for (x, y, w, h) in nose:
+        mustache_resized = cv2.resize(mustache, (w, h))
+        alpha_channel = mustache_resized[:, :, 3] / 255.0
+        
+        mustache_mask = np.zeros_like(mustache_resized[:, :, 3])
+        
+        # Copy alpha channel to mask and apply threshold
+        mustache_mask[mustache_resized[:, :, 3] > 0] = 255
+
+        for c in range(0, 3):
+            frame[y:y+h, x:x+w, c] = (1 - alpha_channel) * frame[y:y+h, x:x+w, c] + alpha_channel * mustache_resized[:, :, c]
+
+    return frame

app.py

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+import cv2
+import numpy as np
+import streamlit as st
+from Code import apply_effects
+
+# Load cascade classifiers and images
+glassesCasc = cv2.CascadeClassifier('Train/third-party/frontalEyes35x16.xml')
+noseCasc = cv2.CascadeClassifier('Train/third-party/Nose18x15.xml')
+glasses = cv2.imread('Train/glasses.png', cv2.IMREAD_UNCHANGED)
+mustache = cv2.imread('Train/mustache.png', cv2.IMREAD_UNCHANGED)
+
+def main():
+    st.title("Snapchat Filter App")
+    st.write("Upload an image or use your webcam to apply face effects!")
+
+    option = st.selectbox("Choose an option", ("Upload Image", "Use Webcam"))
+
+    if option == "Upload Image":
+        uploaded_image = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
+        if uploaded_image is not None:
+            image = cv2.imdecode(np.fromstring(uploaded_image.read(), np.uint8), 1)
+            image_with_effects = apply_effects(image)
+            st.image(image_with_effects, channels="BGR", use_column_width=True)
+
+    else:  # Use Webcam
+        cap = cv2.VideoCapture(0)
+        st.write("Webcam is active.")
+        frame_placeholder = st.empty()
+
+        while cap.isOpened():
+            ret, frame = cap.read()
+            if not ret:
+                break
+            image_with_effects = apply_effects(frame)
+            frame_placeholder.image(image_with_effects, channels="BGR", use_column_width=True)
+
+if __name__ == "__main__":
+    main()

app1.py

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+import cv2
+import numpy as np
+import gradio as gr
+
+# Load the cascade classifiers and images
+glassesCasc = cv2.CascadeClassifier('Train/third-party/frontalEyes35x16.xml')
+noseCasc = cv2.CascadeClassifier('Train/third-party/Nose18x15.xml')
+glasses = cv2.imread('Train/glasses.png', cv2.IMREAD_UNCHANGED)
+mustache = cv2.imread('Train/mustache.png', cv2.IMREAD_UNCHANGED)
+
+def apply_effects(frame):
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    
+    eyes = glassesCasc.detectMultiScale(gray, 1.5, 5, 0)
+    for (x, y, w, h) in eyes:
+        glasses_resized = cv2.resize(glasses, (w, h))
+        alpha_channel = glasses_resized[:, :, 3] / 255.0
+        glasses_mask = np.zeros_like(glasses_resized[:, :, 3])
+        glasses_mask[glasses_resized[:, :, 3] > 0] = 255
+        for c in range(0, 3):
+            frame[y:y+h, x:x+w, c] = (1 - alpha_channel) * frame[y:y+h, x:x+w, c] + alpha_channel * glasses_resized[:, :, c]
+
+    nose = noseCasc.detectMultiScale(gray, 1.3, 5, 0)
+    for (x, y, w, h) in nose:
+        mustache_resized = cv2.resize(mustache, (w, h))
+        alpha_channel = mustache_resized[:, :, 3] / 255.0
+        mustache_mask = np.zeros_like(mustache_resized[:, :, 3])
+        mustache_mask[mustache_resized[:, :, 3] > 0] = 255
+        for c in range(0, 3):
+            frame[y:y+h, x:x+w, c] = (1 - alpha_channel) * frame[y:y+h, x:x+w, c] + alpha_channel * mustache_resized[:, :, c]
+
+    return frame
+
+iface = gr.Interface(fn=apply_effects, inputs="webcam", outputs="image")
+iface.launch()

modelCamera.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "import numpy as np "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "glasses=cv2.imread('Train/glasses.png',cv2.IMREAD_UNCHANGED)\n",
+    "mustache=cv2.imread('Train/mustache.png',cv2.IMREAD_UNCHANGED)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "glassesCasc=cv2.CascadeClassifier('Train/third-party/frontalEyes35x16.xml')\n",
+    "noseCasc=cv2.CascadeClassifier('Train/third-party/Nose18x15.xml')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cap=cv2.VideoCapture(0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "while True:\n",
+    "    ret,frame=cap.read()\n",
+    "    gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)\n",
+    "    eyes = glassesCasc.detectMultiScale(gray, 1.5, 5, 0)\n",
+    "    for (x, y, w, h) in eyes:\n",
+    "        glasses_resized = cv2.resize(glasses, (w, h))\n",
+    "        alpha_channel = glasses_resized[:, :, 3] / 255.0\n",
+    "        \n",
+    "        # Create a mask for the glasses\n",
+    "        glasses_mask = np.zeros_like(glasses_resized[:, :, 3])\n",
+    "        \n",
+    "        # Copy alpha channel to mask and apply threshold\n",
+    "        glasses_mask[glasses_resized[:, :, 3] > 0] = 255\n",
+    "        \n",
+    "        # Overlay the glasses using the mask\n",
+    "        for c in range(0, 3):\n",
+    "            frame[y:y+h, x:x+w, c] = (1 - alpha_channel) * frame[y:y+h, x:x+w, c] + alpha_channel * glasses_resized[:, :, c]\n",
+    "\n",
+    "    nose=noseCasc.detectMultiScale(gray,1.3,5,0)\n",
+    "    for (x, y, w, h) in nose:\n",
+    "        mustache_resized = cv2.resize(mustache, (w, h))\n",
+    "        alpha_channel = mustache_resized[:, :, 3] / 255.0\n",
+    "        \n",
+    "        mustache_mask = np.zeros_like(mustache_resized[:, :, 3])\n",
+    "        \n",
+    "        # Copy alpha channel to mask and apply threshold\n",
+    "        mustache_mask[mustache_resized[:, :, 3] > 0] = 255\n",
+    "\n",
+    "        for c in range(0, 3):\n",
+    "            frame[y:y+h, x:x+w, c] = (1 - alpha_channel) * frame[y:y+h, x:x+w, c] + alpha_channel * mustache_resized[:, :, c]\n",
+    "\n",
+    "    cv2.imshow('Webcam Feed', frame)\n",
+    "\n",
+    "    if cv2.waitKey(1) & 0xFF == ord('q'):\n",
+    "        break\n",
+    "\n",
+    "cap.release()\n",
+    "cv2.destroyAllWindows()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.9"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

modelPicture.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "import numpy as np "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "glasses=cv2.imread('Train/glasses.png',cv2.IMREAD_UNCHANGED)\n",
+    "mustache=cv2.imread('Train/mustache.png',cv2.IMREAD_UNCHANGED)\n",
+    "\n",
+    "frame=cv2.imread('Test/Before.png')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "glassesCasc=cv2.CascadeClassifier('Train/third-party/frontalEyes35x16.xml')\n",
+    "noseCasc=cv2.CascadeClassifier('Train/third-party/Nose18x15.xml')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)\n",
+    "eyes = glassesCasc.detectMultiScale(gray, 1.5, 5, 0)\n",
+    "for (x, y, w, h) in eyes:\n",
+    "    glasses_resized = cv2.resize(glasses, (w, h))\n",
+    "    alpha_channel = glasses_resized[:, :, 3] / 255.0\n",
+    "    \n",
+    "    # Create a mask for the glasses\n",
+    "    glasses_mask = np.zeros_like(glasses_resized[:, :, 3])\n",
+    "    \n",
+    "    # Copy alpha channel to mask and apply threshold\n",
+    "    glasses_mask[glasses_resized[:, :, 3] > 0] = 255\n",
+    "    \n",
+    "    # Overlay the glasses using the mask\n",
+    "    for c in range(0, 3):\n",
+    "        frame[y:y+h, x:x+w, c] = (1 - alpha_channel) * frame[y:y+h, x:x+w, c] + alpha_channel * glasses_resized[:, :, c]\n",
+    "\n",
+    "nose=noseCasc.detectMultiScale(gray,1.1,5,0)\n",
+    "for (x, y, w, h) in nose:\n",
+    "    mustache_resized = cv2.resize(mustache, (w, h))\n",
+    "    alpha_channel = mustache_resized[:, :, 3] / 255.0\n",
+    "    \n",
+    "    mustache_mask = np.zeros_like(mustache_resized[:, :, 3])\n",
+    "    \n",
+    "    # Copy alpha channel to mask and apply threshold\n",
+    "    mustache_mask[mustache_resized[:, :, 3] > 0] = 255\n",
+    "\n",
+    "    for c in range(0, 3):\n",
+    "        frame[y+20:y+h+20, x:x+w, c] = (1 - alpha_channel) * frame[y+20:y+h+20, x:x+w, c] + alpha_channel * mustache_resized[:, :, c]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "flattened_image = frame.reshape(-1, 3)\n",
+    "column_names = ['Channel 1', 'Channel 2', 'Channel 3']\n",
+    "\n",
+    "data_with_headers = np.vstack([column_names, flattened_image])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "np.savetxt('outputImg.csv', data_with_headers, delimiter=',', fmt='%s')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.9"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

tempCodeRunnerFile.python

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+# %%
+import cv2
+import numpy as np 
+
+# %%
+glasses=cv2.imread('Train/glasses.png',cv2.IMREAD_UNCHANGED)
+mustache=cv2.imread('Train/mustache.png',cv2.IMREAD_UNCHANGED)
+
+# %%
+glassesCasc=cv2.CascadeClassifier('Train/third-party/frontalEyes35x16.xml')
+noseCasc=cv2.CascadeClassifier('Train/third-party/Nose18x15.xml')
+
+def camera():
+    cap=cv2.VideoCapture(0)
+    while True:
+        ret,frame=cap.read()
+        gray=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
+        eyes = glassesCasc.detectMultiScale(gray, 1.5, 5, 0)
+        for (x, y, w, h) in eyes:
+            glasses_resized = cv2.resize(glasses, (w, h))
+            alpha_channel = glasses_resized[:, :, 3] / 255.0
+            
+            # Create a mask for the glasses
+            glasses_mask = np.zeros_like(glasses_resized[:, :, 3])
+            
+            # Copy alpha channel to mask and apply threshold
+            glasses_mask[glasses_resized[:, :, 3] > 0] = 255
+            
+            # Overlay the glasses using the mask
+            for c in range(0, 3):
+                frame[y:y+h, x:x+w, c] = (1 - alpha_channel) * frame[y:y+h, x:x+w, c] + alpha_channel * glasses_resized[:, :, c]
+
+        nose=noseCasc.detectMultiScale(gray,1.1,5,0)
+        for (x, y, w, h) in nose:
+            mustache_resized = cv2.resize(mustache, (w, h))
+            alpha_channel = mustache_resized[:, :, 3] / 255.0
+            
+            mustache_mask = np.zeros_like(mustache_resized[:, :, 3])
+            
+            # Copy alpha channel to mask and apply threshold
+            mustache_mask[mustache_resized[:, :, 3] > 0] = 255
+
+            for c in range(0, 3):
+                frame[y:y+h, x:x+w, c] = (1 - alpha_channel) * frame[y:y+h, x:x+w, c] + alpha_channel * mustache_resized[:, :, c]
+
+        cv2.imshow('Webcam Feed', frame)
+
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+
+    cap.release()
+    cv2.destroyAllWindows()
+
+camera()
+
+