Deep Learning model to switch cameras
datasets/
frames/
surgery_01/
000000.npy
...
surgery_02/
labels/
surgery_01.csv
surgery_02.csv
meta/
meta_file.yml
raw_frame/
surgery_01/
000000.jpg
...
surgery_02/
raw_video/
surgery_01/
0.mp4
...
4.mp4
run the script to generate npy and jpg files (for visualization) of surgery (surgery_01) before training the model.
python switching/data_process/process_video_raw.py --surgery_id surgery_01
To train the model with configuration file (model_01) run the script file below.
python switching/train.py --cfg model_01
TO resume the training from some iteration (iteration=500), run the script file below.
python switching/train.py --cfg model_01 --iter 500
After training the model (with cfg), results are saved with the following folder structure.
results/
model_01/
log/
models/
results/
tb/
The testing is done like this.
python swtiching/train.py --cfg model_01 --mode test --data test --iter 500
The results are saved under the folder results/model_01/results