yahskapar
commented
1 week ago Hi @zzl0318,
It's totally possible training on UBFC-Phys is quite unstable, personally I've never even tried and only used it as an evaluation dataset in the past. Try tweaking things like using RetinaFace instead of Haar Cascade for the face detection backend, as well as enabling dynamic detection and utilizing a median face box. UBFC-Phys has quite a bit of rigid head motion that can be significantly influenced by face detection-related parameters.
If that doesn't work at all, it's also worth playing around with the more general hyperparameters (e.g., learning rate, epochs) as well.
All the best,
Akshay
I tried a config like this, but the results was very pore. Is their something wrong with my config file? Calculating metrics! 100%|███████████████████████████████████████████| 42/42 [00:30<00:00, 1.38it/s] FFT MAE (FFT Label): 34.005301339285715 +/- 3.033595794199921 FFT RMSE (FFT Label): 39.27943563449327 +/- 14.6103528726731 FFT MAPE (FFT Label): 31.529103551082756 +/- 2.462837199273431 FFT Pearson (FFT Label): -0.07576602068851186 +/- 0.15765940426351263 FFT SNR (FFT Label): -12.177335893780446 +/- 1.1786350898544593 (dB)
BASE: [''] TOOLBOX_MODE: "train_and_test" # "train_and_test" or "only_test" TRAIN: BATCH_SIZE: 4 EPOCHS: 30 LR: 9e-3 MODEL_FILE_NAME: PURE_PURE_UBFC_tscan PLOT_LOSSES_AND_LR: True DATA: FILTERING: USE_EXCLUSION_LIST: True EXCLUSION_LIST: [ 's3_T1', 's8_T1', 's9_T1', 's26_T1', 's28_T1', 's30_T1', 's31_T1', 's32_T1', 's33_T1', 's40_T1', 's52_T1', 's53_T1', 's54_T1', 's56_T1', 's1_T2', 's4_T2', 's6_T2', 's8_T2', 's9_T2', 's11_T2', 's12_T2', 's13_T2', 's14_T2', 's19_T2', 's21_T2', 's22_T2', 's25_T2', 's26_T2', 's27_T2', 's28_T2', 's31_T2', 's32_T2', 's33_T2', 's35_T2', 's38_T2', 's39_T2', 's41_T2', 's42_T2', 's45_T2', 's47_T2', 's48_T2', 's52_T2', 's53_T2', 's55_T2', 's5_T3', 's8_T3', 's9_T3', 's10_T3', 's13_T3', 's14_T3', 's17_T3', 's22_T3', 's25_T3', 's26_T3', 's28_T3', 's30_T3', 's32_T3', 's33_T3', 's35_T3', 's37_T3', 's40_T3', 's47_T3', 's48_T3', 's49_T3', 's50_T3', 's52_T3', 's53_T3'] SELECT_TASKS: True TASK_LIST: ['T1', 'T2', 'T3'] FS: 35 DATASET: UBFC-PHYS DO_PREPROCESS: True # if first time, should be true DATA_FORMAT: NDCHW DATA_PATH: "/mnt/newdisk/rppg_datasets/UBFC-Phys-raw" # Raw dataset path, need to be updated CACHED_PATH: "/home/zzl/rPPG-Toolbox/dataset/UBFC-Pyhs-preprocessed" # Processed dataset save path, need to be updated EXP_DATA_NAME: "" BEGIN: 0.0 END: 0.8 PREPROCESS: DATA_TYPE: ['DiffNormalized','Standardized'] DATA_AUG: ['None'] # 'None' or 'Motion' is supported, used if the data path points to an augmented dataset or requires augmentation LABEL_TYPE: DiffNormalized DO_CHUNK: True CHUNK_LENGTH: 180 CROP_FACE: DO_CROP_FACE: True BACKEND: 'HC' # HC for Haar Cascade, RF for RetinaFace USE_LARGE_FACE_BOX: True LARGE_BOX_COEF: 1.5 DETECTION: DO_DYNAMIC_DETECTION: False DYNAMIC_DETECTION_FREQUENCY: 30 USE_MEDIAN_FACE_BOX: False # This should be used ONLY if dynamic detection is used RESIZE: H: 72 W: 72 VALID: DATA: FS: 30 DATASET: UBFC-PHYS DO_PREPROCESS: False # if first time, should be true DATA_FORMAT: NDCHW DATA_PATH: "/mnt/newdisk/rppg_datasets/UBFC-Phys-raw" # Raw dataset path, need to be updated CACHED_PATH: "/home/zzl/rPPG-Toolbox/dataset/UBFC-Pyhs-preprocessed" # Processed dataset save path, need to be updated EXP_DATA_NAME: "" BEGIN: 0.8 END: 1.0 PREPROCESS: DATA_TYPE: [ 'DiffNormalized','Standardized' ] DATA_AUG: ['None'] # 'None' or 'Motion' is supported, used if the data path points to an augmented dataset or requires augmentation LABEL_TYPE: DiffNormalized DO_CHUNK: True CHUNK_LENGTH: 180 CROP_FACE: DO_CROP_FACE: True BACKEND: 'HC' # HC for Haar Cascade, RF for RetinaFace USE_LARGE_FACE_BOX: True LARGE_BOX_COEF: 1.5 DETECTION: DO_DYNAMIC_DETECTION: False DYNAMIC_DETECTION_FREQUENCY : 30 USE_MEDIAN_FACE_BOX: False # This should be used ONLY if dynamic detection is used RESIZE: H: 72 W: 72 TEST: METRICS: ['MAE', 'RMSE', 'MAPE', 'Pearson', 'SNR', 'BA'] USE_LAST_EPOCH: True # to use provided validation dataset to find the best epoch, should be false DATA: FS: 30 DATASET: UBFC-rPPG DO_PREPROCESS: True # if first time, should be true DATA_FORMAT: NDCHW DATA_PATH: "/mnt/newdisk/rppg_datasets/UBFC-rPPG-raw" # need to be updated CACHED_PATH: "/home/zzl/rPPG-Toolbox/dataset/ubfc-rppg-preprocessed" # Processed dataset save path, need to be updated EXP_DATA_NAME: "" BEGIN: 0.0 END: 1.0 PREPROCESS: DATA_TYPE: [ 'DiffNormalized','Standardized' ] LABEL_TYPE: DiffNormalized DO_CHUNK: True CHUNK_LENGTH: 180 CROP_FACE: DO_CROP_FACE: True BACKEND: 'HC' # HC for Haar Cascade, RF for RetinaFace USE_LARGE_FACE_BOX: True LARGE_BOX_COEF: 1.5 DETECTION: DO_DYNAMIC_DETECTION: False DYNAMIC_DETECTION_FREQUENCY: 30 USE_MEDIAN_FACE_BOX: False # This should be used ONLY if dynamic detection is used RESIZE: H: 72 W: 72 DEVICE: cuda:0 NUM_OF_GPU_TRAIN: 1 LOG: PATH: runs/exp MODEL: DROP_RATE: 0.2 NAME: Tscan TSCAN: FRAME_DEPTH: 10 INFERENCE: BATCH_SIZE: 4 EVALUATION_METHOD: "FFT" # "FFT" or "peak detection" EVALUATION_WINDOW: USE_SMALLER_WINDOW: False # Change this if you'd like an evaluation window smaller than the test video length WINDOW_SIZE: 10 # In seconds MODEL_PATH: ""