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import gradio as gr
import cv2
import numpy as np
def remove_green_screen(video):
def process_frame(frame):
# Convert to HSV color space
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
# Define the range of green color
lower_green = np.array([25, 52, 72])
upper_green = np.array([102, 255, 255])
# Threshold the HSV image to get only green colors
mask = cv2.inRange(hsv, lower_green, upper_green)
# Bitwise-AND mask and original image
res = cv2.bitwise_and(frame, frame, mask=mask)
return res
# Load background image
bg_image = cv2.imread("background.jpg")
# Open video file
cap = cv2.VideoCapture(video)
# Get video codec and fps
fourcc = int(cap.get(cv2.CAP_PROP_FOURCC))
fps = int(cap.get(cv2.CAP_PROP_FPS))
# Get video dimensions
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
# Create output video writer
out = cv2.VideoWriter("output.mp4", fourcc, fps, (width, height))
frames = []
# Loop through video frames
while True:
ret, frame = cap.read()
if not ret:
break
# Process frame
bg = cv2.imread(bg_image)
frames.append(process_frame(frame))
# Release video file and output video writer
cap.release()
out.release()
# Write output video
out = cv2.VideoWriter("output.mp4", fourcc, fps, (width, height))
for frame in frames:
out.write(frame)
out.release()
return "output.mp4"
input_video = gr.inputs.Video(label="Input Video")
outputs = gr.outputs.Video(label="Processed Video", type="mp4")
gr.Interface(remove_green_screen, inputs=input_video, outputs=outputs).launch()
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