training and testing ONSET model on Market1501 dataset, creating visu…

scripts/default_config.py

@@ -99,11 +99,11 @@ def get_default_config():
     cfg.test.dist_metric = 'euclidean' # distance metric, ['euclidean', 'cosine']
     cfg.test.normalize_feature = False # normalize feature vectors before computing distance
     cfg.test.ranks = [1, 5, 10, 20] # cmc ranks
-    cfg.test.evaluate = False # test only
+    cfg.test.evaluate = True # True: test only --   False: train and test     f
     cfg.test.eval_freq = -1 # evaluation frequency (-1 means to only test after training)
     cfg.test.start_eval = 0 # start to evaluate after a specific epoch
     cfg.test.rerank = False # use person re-ranking
-    cfg.test.visrank = False # visualize ranked results (only available when cfg.test.evaluate=True)
+    cfg.test.visrank = True # visualize ranked results (only available when cfg.test.evaluate=True)
     cfg.test.visrank_topk = 10 # top-k ranks to visualize
 
     return cfg

torchreid/data/datasets/image/market1501.py

@@ -21,12 +21,12 @@ class Market1501(ImageDataset):
     """
     _junk_pids = [0, -1]
     dataset_dir = 'market1501'
-    dataset_url = 'http://188.138.127.15:81/Datasets/Market-1501-v15.09.15.zip'
+    # dataset_url = 'http://188.138.127.15:81/Datasets/Market-1501-v15.09.15.zip'
 
     def __init__(self, root='', market1501_500k=False, **kwargs):
         self.root = osp.abspath(osp.expanduser(root))
         self.dataset_dir = osp.join(self.root, self.dataset_dir)
-        self.download_dataset(self.dataset_dir, self.dataset_url)
+        # self.download_dataset(self.dataset_dir, self.dataset_url)
 
         # allow alternative directory structure
         self.data_dir = self.dataset_dir