Delete test_multicard.py

test_multicard.py

@@ -1,99 +0,0 @@
-import time, os, torch, argparse, warnings, glob, pandas, json
-
-from utils.tools import *
-from dlhammer import bootstrap
-
-from dataLoader_multiperson import val_loader
-from loconet import loconet
-
-
-class DataPrep():
-
-    def __init__(self, cfg):
-        self.cfg = cfg
-
-    def val_dataloader(self):
-        cfg = self.cfg
-        loader = val_loader(cfg, trialFileName = cfg.evalTrialAVA, \
-                            audioPath     = os.path.join(cfg.audioPathAVA , cfg.evalDataType), \
-                            visualPath    = os.path.join(cfg.visualPathAVA, cfg.evalDataType), \
-                            num_speakers=cfg.MODEL.NUM_SPEAKERS,
-                            )
-        valLoader = torch.utils.data.DataLoader(loader,
-                                                batch_size=cfg.VAL.BATCH_SIZE,
-                                                shuffle=False,
-                                                num_workers=16)
-        return valLoader
-
-
-def prepare_context_files(cfg):
-    path = os.path.join(cfg.DATA.dataPathAVA, "csv")
-    for phase in ["val", "test"]:
-        csv_f = f"{phase}_loader.csv"
-        csv_orig = f"{phase}_orig.csv"
-        entity_f = os.path.join(path, phase + "_entity.json")
-        ts_f = os.path.join(path, phase + "_ts.json")
-        if os.path.exists(entity_f) and os.path.exists(ts_f):
-            continue
-        orig_df = pandas.read_csv(os.path.join(path, csv_orig))
-        entity_data = {}
-        ts_to_entity = {}
-
-        for index, row in orig_df.iterrows():
-
-            entity_id = row['entity_id']
-            video_id = row['video_id']
-            if row['label'] == "SPEAKING_AUDIBLE":
-                label = 1
-            else:
-                label = 0
-            ts = float(row['frame_timestamp'])
-            if video_id not in entity_data.keys():
-                entity_data[video_id] = {}
-            if entity_id not in entity_data[video_id].keys():
-                entity_data[video_id][entity_id] = {}
-            if ts not in entity_data[video_id][entity_id].keys():
-                entity_data[video_id][entity_id][ts] = []
-
-            entity_data[video_id][entity_id][ts] = label
-
-            if video_id not in ts_to_entity.keys():
-                ts_to_entity[video_id] = {}
-            if ts not in ts_to_entity[video_id].keys():
-                ts_to_entity[video_id][ts] = []
-            ts_to_entity[video_id][ts].append(entity_id)
-
-        with open(entity_f) as f:
-            json.dump(entity_data, f)
-
-        with open(ts_f) as f:
-            json.dump(ts_to_entity, f)
-
-
-def main():
-    cfg = bootstrap(print_cfg=False)
-    print(cfg)
-    epoch = cfg.RESUME_EPOCH
-
-    warnings.filterwarnings("ignore")
-
-    cfg = init_args(cfg)
-
-    data = DataPrep(cfg)
-
-    prepare_context_files(cfg)
-
-    if cfg.downloadAVA == True:
-        preprocess_AVA(cfg)
-        quit()
-
-    s = loconet(cfg)
-
-    s.loadParameters(cfg.RESUME_PATH)
-    mAP = s.evaluate_network(epoch=epoch, loader=data.val_dataloader())
-    print(f"evaluate ckpt: {cfg.RESUME_PATH}")
-    print(mAP)
-
-
-if __name__ == '__main__':
-    main()