get annot

data_loader.py

+from logger import Logger
+import torch
+import torchvision.transforms as transforms
+from PIL import Image
+import numpy as np
+LOGGER = Logger().logger()
+#Author: @meetdoshi
+from Utils import device
+from  data_utils import PinDataset
+
+class DataLoader():
+    def __init__(self):
+        self.pin_dataset = PinDataset(partitions=range(1))
+        self.pin_dataset.load_meta_data()
+        self.pidxs = self.pin_dataset.get_pidxs()
+        return
+
+    def get_sample_image(self):
+        '''
+        Function to get image,anno
+        '''
+        pidx = np.random.choice(self.pidxs)
+        print(pidx,type(pidx))
+        image, anno = self.pin_dataset.get_annotation(pin_id=pidx)
+        return image,anno
+
+    def get_all_images(self):
+        '''
+        Function to get all images
+        '''
+        images = []
+        annotations = []
+        for pidx in self.pidxs:
+            print(pidx)
+            image,anno = self.pin_dataset.get_annotation(pin_id=pidx)
+            images.append(image)
+            annotations.append(anno)
+        return images,annotations
+'''
+if __name__ == "__main__":
+    data_loader = DataLoader()
+    image,anno = data_loader.get_sample_image()
+    print(image,type(image))
+    print(anno)
+'''

data_utils.py

@@ -148,7 +148,7 @@ class PinDataset(object):
     annos = []
     pidxs = {}
     for meta_path in self.meta_paths:
-      annos.extend(np.load(meta_path).tolist())
+      annos.extend(np.load(meta_path,allow_pickle=True,encoding='latin1').tolist())
     print('Meta data loaded, contains %d images.' % len(annos))
     for (ind_a, anno) in enumerate(annos):
       pidx = self._get_pidx_from_image_name(anno['image_name'])
@@ -161,7 +161,7 @@ class PinDataset(object):
   def get_pidxs(self, max_return_num=None):
     """Return the list of pinterest image idx in the meta data."""
     assert self.annos is not None, 'Load meta data first, call load_meta_data()'
-    pidxs_list = list(self.pidxs.iterkeys())
+    pidxs_list = list(i for i in self.pidxs)
     if max_return_num is not None:
       num = min(len(pidxs_list), max_return_num)
     else:

download_images.py

@@ -11,7 +11,8 @@ from __future__ import division
 from __future__ import print_function
 
 from data_utils import PinDataset
-
+'''
 if __name__ == '__main__':
   pin_dataset = PinDataset()
   pin_dataset.download_images()
+'''

model.py

@@ -2,6 +2,7 @@ import numpy as np
 import torch
 import torch.nn as nn
 from logger import Logger
+from data_loader import DataLoader
 LOGGER = Logger().logger()
 
 class Model():