issue activeloopai#106 MPII Human Pose Dataset example added

Gyanachand1 · Nov 1, 2020 · 3bbd0db · 3bbd0db
1 parent 31788fe
commit 3bbd0db
Showing 1 changed file with 22 additions and 20 deletions.
diff --git a/examples/MPII Human Pose Dataset/mpii_data_upload.py b/examples/MPII Human Pose Dataset/mpii_data_upload.py
@@ -10,20 +10,18 @@
 
 
 class MPIIGenerator(dataset.DatasetGenerator):
-    '''
+    """
     Purpose of generator class is to return dictionary of arrays for the individual example.
     This class inherites from dataset.DatasetGenerator so it is called iteratively for the
     number of examples present in dataset.
-    
     We have defined two functions here:    
     meta: returns keys of the dictinary which are refered as features and labels of dataset.
-    
     __call__ : this function takes the list of features(annotations in this case)as input and
     adds the features(or labels) according to the keys in a row of dataset.
-    '''
+    """
 
     def meta(self):
-        
+
         return {
             "image": {"shape": (1,), "dtype": "object", "chunksize": 1000},
             "dataset": {"shape": (1,), "dtype": "object", "chunksize": 1000},
@@ -35,7 +33,11 @@ def meta(self):
             "joint_self": {"shape": (1,), "dtype": "object", "chunksize": 1000},
             "scale_provided": {"shape": (1,), "dtype": "object", "chunksize": 1000},
             "joint_others": {"shape": (1,), "dtype": "object", "chunksize": 1000},
-            "scale_provided_other": {"shape": (1,), "dtype": "object", "chunksize": 1000},
+            "scale_provided_other": {
+                "shape": (1,),
+                "dtype": "object",
+                "chunksize": 1000
+                },
             "objpos_other": {"shape": (1,), "dtype": "object", "chunksize": 1000},
             "annolist_index": {"shape": (1,), "dtype": "object", "chunksize": 1000},
             "people_index": {"shape": (1,), "dtype": "object", "chunksize": 1000},
@@ -47,8 +49,8 @@ def __call__(self, input):
         try:
             ds = {}
             img_path = '/home/sanchit/images/'
-            
-            n = 1                   # for 1 row
+
+            n = 1  # for 1 row
             ds["image"] = np.empty(n, object)
             ds["dataset"] = np.empty(n, object)
             ds["isValidation"] = np.empty(n, object)
@@ -64,18 +66,18 @@ def __call__(self, input):
             ds["annolist_index"] = np.empty(n, object)
             ds["people_index"] = np.empty(n, object)
             ds["numOtherPeople"] = np.empty(n, object)
-            
-            i = 0                   # i = 0 for 1st row, i changes iteratively.
+
+            i = 0  # i = 0 for 1st row, i changes iteratively.
             ds["image"][i] = np.array(Image.open(img_path + input['img_paths']))
             ds["dataset"][i] = input['dataset']
             ds["isValidation"][i] = input['isValidation']
             ds["img_paths"][i] = input['img_paths']
             ds['img_width'][i] = input['img_width']
             ds["img_height"][i] = input['img_height']
-            '''
+            """
             Some features in input list has another list(more than one list) inside them.
             So they are converted to array using np.array(list(list()).
-            '''
+            """
             ds["objpos"][i] = np.array(input['objpos'])   
             ds["joint_self"][i] = np.array(input['joint_self'])
             ds["scale_provided"][i] = input['scale_provided']
@@ -87,19 +89,19 @@ def __call__(self, input):
             ds["numOtherPeople"][i] = input['numOtherPeople']
 
             return ds
-        
+
         except Exception as e:
             logger.error(e, exc_info=e, stack_info=True)
 
 def load_dataset():
-    '''
+    """
     This function is used to load json annotations in the form of dictionary and then
     appending all the dictionaries(25205 examples) in the list named annotations.
     Then this list is given as input to __call__ function of generator class.
     dataset.generate calls the generator class iteratively for each dictionary present
     in the list(annotations). Finally it returns the complete dataset with all examples.
-    '''
-    
+    """
+
     with open('/home/sanchit/mpii_annotations.json',"r") as f:
 
         instances = json.load(f)
@@ -109,18 +111,18 @@ def load_dataset():
     for i in range(len(instances)):
         annotations.append(instances[i])
 
-#    print(annotations[:5])
+    #   print(annotations[:5])
     print("Annotations loaded.")
-    
+
     ds = dataset.generate(MPIIGenerator(), annotations)
     print("Dataset generated.")
-    
+
     return ds
 
 def main():
 
     t1 = time.time()
-    # Call the load_dataset function to generate the complete dataset.
+    # Call the load_dataset function to generate the complete dataset
     ds = load_dataset()
     # ds.store stores the dataset in "username/MPII_Human_Pose_Dataset"
     ds.store("MPII_Human_Pose_Dataset")