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video_processing_mmsegmentation.py
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import traceback
import cv2
import numpy as np
import sys
import argparse
from datetime import datetime
import os
# MMSegmentation is an open source semantic segmentation toolbox based on PyTorch. It is a part of the OpenMMLab project.
# https://github.com/open-mmlab/mmsegmentation
# Install steps:
# wget https://download.openmmlab.com/mmsegmentation/v0.5/deeplabv3plus/deeplabv3plus_r101b-d8_769x769_80k_cityscapes/deeplabv3plus_r101b-d8_769x769_80k_cityscapes_20201226_205041-227cdf7c.pth
# Status: not working
pathToProject='../mmsegmentation/'
sys.path.insert(0, pathToProject)
os.chdir(pathToProject)
import torch
from mmdet.apis import inference_detector, init_detector
def init_model(transform):
parser = argparse.ArgumentParser(description='MMDetection webcam demo')
parser.add_argument('config', help='test config file path', default='./configs/deeplabv3plus/deeplabv3plus_r101b-d8_769x769_80k_cityscapes.py')
parser.add_argument('checkpoint', help='checkpoint file', default='deeplabv3plus_r101b-d8_769x769_80k_cityscapes_20201226_205041-227cdf7c.pth')
parser.add_argument(
'--device', type=str, default='cuda:0', help='CPU/CUDA device option')
parser.add_argument(
'--camera-id', type=int, default=0, help='camera device id')
parser.add_argument(
'--score-thr', type=float, default=0.5, help='bbox score threshold')
args = parser.parse_known_args()
device = torch.device(args.device)
model = init_detector(args.config, args.checkpoint, device=device)
return (device,model),None
def process_image(transform,processing_model,img):
tracks = []
try:
(device,model) = processing_model
result = inference_detector(model, img)
model.show_result(
img, result, score_thr=args.score_thr, wait_time=1, show=True)
except Exception as e:
track = traceback.format_exc()
print(track)
print("MMDetection Exception",e)
pass
return tracks,img