train with own co-occurrence matrix

ck-amrahd · Apr 23, 2020 · 698dd41 · 698dd41
1 parent c98c6d7
commit 698dd41
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Showing 8 changed files with 1 addition and 44 deletions.
diff --git a/.gitignore b/.gitignore
@@ -1,3 +1,4 @@
 venv
 *.pyc
 data/yolov3.weights
+__pycache__
diff --git a/Results/model.pth b/Results/model.pth
diff --git a/Results/model_old.pth b/Results/model_old.pth
diff --git a/data/coco_adj.pkl b/data/coco_adj.pkl
diff --git a/data/coco_glove_word2vec.pkl b/data/coco_glove_word2vec.pkl
diff --git a/test_pickle.py b/test_pickle.py
diff --git a/train.py b/train.py
@@ -7,7 +7,6 @@
 from dataset import CocoDataset
 from torch.utils.data import DataLoader
 import pickle
-from utils import generate_adjacency_matrix
 import numpy as np
 
 device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
@@ -21,9 +20,6 @@
 val_path = '/home/user/Data/coco2014/val2014'
 val_ann_file = '/home/user/Data/coco2014/annotations/instances_val2014.json'
 
-# adj = pickle.load(open('data/coco_adj.pkl', 'rb'))
-# adj = np.float32(generate_adjacency_matrix(adj))
-
 adj = pickle.load(open('adj.pickle', 'rb'))
 adj = np.float32(adj / np.max(adj) + np.identity(num_classes))
 

diff --git a/utils.py b/utils.py
@@ -104,23 +104,3 @@ def tensor_to_image(img_tensor):
     # img = np.clip(img, 0, 1)
     return img
 
-
-def generate_adjacency_matrix(adj_file):
-    nums = adj_file['nums']
-    adj = adj_file['adj']
-
-    nums = nums[:, np.newaxis]
-
-    adj = adj / nums
-
-    adj[adj < 0.5] = 0
-    adj[adj >= 0.5] = 1
-
-    adj = adj * 0.25 / (np.sum(adj, axis=0, keepdims=True) + 1e-6)
-    A = adj + np.identity(80, np.int)
-
-    D = np.power(np.sum(A, axis=1), -0.5)
-    D = np.diag(D)
-
-    adj = np.matmul(np.matmul(A, D).T, D)
-    return adj