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import cv2
import os.path
# from frame_do_video import images_to_video
import numpy as np
from ultralytics import YOLO
from file_utils import project_dir
def train():
"""
Funksiya modelni train qiladi
data uyidagi formatda bo'lish kerak
# - splitted
# - train
# - good
# - problem
# - val
# - good
# - problem
"""
data_joyi = 'traffic_laws/scripts/splitted/'
model = YOLO('yolov8n-cls.pt')
model.train(data=data_joyi, epochs=100, imgsz=224, batch=512, save_period=10, device='cuda:0', augment=True)
metrics = model.val()
print(metrics.top1) # top1 aniqligi
def tekshirish(path2,which_mdel=True):
"""
test qilish, model va rasmni berishimiz kerak
"""
train_qilingan_model_joyi = os.path.join(
project_dir(),
"models",
"classification",
"tl-14",
"weights/best.pt"
)
my_model="tl-14"
if not which_mdel:
my_model="128_1_90"
test_rasm_joyi =(path2)
model_custom = YOLO("models/classification/"+my_model+"/weights/best.pt")
natijalar = model_custom(test_rasm_joyi) # predict on an image
natija = natijalar[0].names[np.argmax(natijalar[0].probs.cpu().numpy().data)]
return (f"Label natija: {natija}")
def process(video_path,which_model):
# saqlash_path = video_path.split('/')[-1].split(".")[0]
saqlash_path = "assets/images"
problem_frame = 0
good_frame = 0
print("currnet path: ", os.getcwd())
if not os.path.exists(saqlash_path):
# Create a new directory because it does not exist
os.makedirs(saqlash_path)
if not os.path.exists(saqlash_path):
raise Exception("Sorry, no numbers below zero")
cap = cv2.VideoCapture(video_path)
saqlash_path="assets/images"
fourcc = cv2.VideoWriter_fourcc(*'XVID')
# out = cv2.VideoWriter('output.avi', fourcc, 20.0, (640,480))
out = cv2.VideoWriter(
saqlash_path, fourcc, 20.0, (int(cap.get(3)), int(cap.get(4)))
)
while(cap.isOpened()):
ret, frame = cap.read()
if ret==True:
#frame = cv2.flip(frame,1)
# print(tekshirish(frame))
if tekshirish(frame,which_model) == "Label natija: good":
font = cv2.FONT_HERSHEY_COMPLEX
cv2.putText(frame, 'good', (0, 100), font, 2, (255, 255, 255), 3)
good_frame += 1
elif tekshirish(frame, which_model) == "Label natija: problem":
font = cv2.FONT_HERSHEY_COMPLEX
cv2.putText(frame, 'problem', (0, 100), font, 2, (255, 255, 255), 3)
# out.write(frame)
cv2.imwrite(saqlash_path + "/%#05d.jpg" % problem_frame, frame)
problem_frame += 1
# cv2.imshow('frame' ,frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
else:
break
cap.release()
out.release()
cv2.destroyAllWindows()
# images_to_video(saqlash_path, video_name = saqlash_path+'_problem.mp4', fps = 24)
return problem_frame,good_frame,saqlash_path
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