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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",
live=True, # This enables the live webcam feed
capture_session=True # This ensures the webcam feed is properly closed when the interface is closed
)
iface.launch()
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