<jupyter_start><jupyter_text>Run Code<jupyter_code>%cd Project_Vision/
!sed -i '/-With-A-Puffy-Jacket-Boots-And-A-Belt.jpg/d' data/customdata/train.txt
#!sed -i '1,10!d' data/customdata/train.txt 
#!sed -i '1,10!d' data/customdata/test.txt
!git pull -f
from options import *
import sys
sys.argv = ['']
plane_args = plane_parse_args()
yolo_args = yolo_parse_args()
midas_args = midas_parse_args()

yolo_args.batch_size = 1

yolo_args.cfg = 'bbox_decoder/cfg/yolov3-custom.cfg'
yolo_args.epochs = 10
yolo_args.weights = '/content/gdrive/My Drive/EVA/EVA5/yolov3-spp-ultralytics.pt'
yolo_args.data = 'data/customdata/custom.data'
midas_args.input = 'data/customdata/images'
#midas_args.output
midas_args.weights = 'midas/model-f6b98070.pt'

plane_args.customDataFolder = 'data/customdata/images'
plane_args.checkpoint_dir = 'planercnn_normal_warping_refine'
plane_args.suffix = 'warping_refine'

yolo_args.img_size=[512,512,512] #[640,640,640]
#yolo_args.img_size=[256,256,256] #[640,640,640]
plane_args.height = 512
plane_args.width = 512
plane_args.test_dir = 'test'
%matplotlib inline
from train import train
loss = train(plane_args,yolo_args,midas_args,add_plane_loss=1,add_yolo_loss=1,add_midas_loss=1,resume_train=True,model_path='/content/gdrive/My Drive/EVA/EVA5/capstone/')
%debug
#from torchsummary import summary

#summary(model2, (3, 256, 256))<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14099783080260303, 'fraction_numerical': 0.052060737527114966, 'mean_word_length': 6.775280898876405, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '82581', 'license': 'MIT', 'n_tokens_mistral': 623, 'n_tokens_neox': 582, 'n_words': 80, 'path': 'Project_vision_Training_Part1.ipynb', 'repo_name': 'vigneshbabupj/Project_Vision', 'size': '1383'}