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from ultralytics import YOLO
import cv2
from PIL import Image
import time
import numpy as np
import uuid
model = YOLO("model/yolo11n_6-2-25.pt")
def draw_boxes(frame, results):
for r in results:
boxes = r.boxes
for box in boxes:
x1, y1, x2, y2 = box.xyxy[0]
x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
cv2.rectangle(frame, (x1, y1), (x2, y2), (255, 0, 255), 3)
cls = r.names[box.cls[0].item()]
# object details
org = [x1, y1]
font = cv2.FONT_HERSHEY_SIMPLEX
fontScale = 1
color = (255, 0, 0)
thickness = 2
cv2.putText(frame, cls, org, font, fontScale, color, thickness)
return frame
def video_detection(cap):
frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
fps = int(cap.get(cv2.CAP_PROP_FPS))
cap = cv2.VideoCapture(video)
video_codec = cv2.VideoWriter_fourcc(*"mp4v") # type: ignore
fps = int(cap.get(cv2.CAP_PROP_FPS))
desired_fps = fps // SUBSAMPLE
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) // 2
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) // 2
iterating, frame = cap.read()
n_frames = 0
name = f"output_{uuid.uuid4()}.mp4"
segment_file = cv2.VideoWriter(name, video_codec, desired_fps, (width, height)) # type: ignore
batch = []
"""
#@spaces.GPU
def video_detection(cap):
frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
fps = int(cap.get(cv2.CAP_PROP_FPS))
out = cv2.VideoWriter('output_video.mp4', cv2.VideoWriter_fourcc(*'h264'), fps, (frame_width, frame_height))
count = 0
while cap.isOpened():
success, frame = cap.read()
if not success:
break
#results = model(frame, stream=True, device='cuda', verbose=False)
results = model(frame, stream=True)
frame = draw_boxes(frame, results)
out.write(frame)
#if not count % 10:
yield frame, None
# print(count)
count += 1
cap.release()
out.release()
cv2.destroyAllWindows()
yield None, 'output_video.mp4'
"""
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