DecentMakeover

import torch
from torch.autograd import Variable
import tools.utils as utils
import tools.dataset as dataset
from PIL import Image
from collections import OrderedDict
import cv2
from models.moran import MORAN

model_path = '/home/ryan/Downloads/2000_0.8805.pth'

DecentMakeover

https://gist.github.com/DecentMakeover/23d9b84b698f7acf6ccb85ff201205d7

DecentMakeover

frames =5
video_folder = '/media/ryan/shakira/3d-cnn-action-recognition/some_folder'
for file in os.listdir(video_folder):
   if file.endswith('.webm'):
       os.mkdir(os.path.join(video_folder,file.split('.')[0]))
       folder_name = file.split('.')[0]
       os.system('ffmpeg -t 4 -i {} -vf fps={} {}/%05d.jpg -t 10'.format(os.path.join(video_folder,file), frames,os.path.join(video_folder,folder_name )))
   elif file.endswith('.mp4'):
       os.mkdir(os.path.join(video_folder,file.split('.')[0]))
       folder_name = file.split('.')[0]

DecentMakeover

import torch.nn as nn
import torch

class Modified3DUNet(nn.Module):
	def __init__(self, in_channels, n_classes, base_n_filter = 8):
		super(Modified3DUNet, self).__init__()
		self.in_channels = in_channels
		self.n_classes = n_classes
		self.base_n_filter = base_n_filter