Update README.md

Author: utkuozbulak

README.md

@@ -39,7 +39,7 @@ This is the skeleton that you have to fill to have a custom dataset. A dataset m
 * `__init__()` function is where the initial logic happens like reading a csv, assigning transforms etc.
 * `__getitem__()` function returns the data and labels. This function is called from dataloader like this:
 ```python
-img, label = CustomDataset.__getitem__(99) # For 99th item
+img, label = MyCustomDataset.__getitem__(99) # For 99th item
 ```
 So, the index parameter is the **n**th data/image (as tensor) you are going to return.
 
@@ -60,14 +60,14 @@ class MyCustomDataset(Dataset):
  def __init__(self, ..., transforms=None):
  # stuff
  ...
- self.transform = transform
+ self.transforms = transforms
 
  def __getitem__(self, index):
  # stuff
  ...
  data = # Some data read from a file or image
- if self.transform is not None:
- data = self.transform(data)
+ if self.transforms is not None:
+ data = self.transforms(data)
  # If the transform variable is not empty
  # then it applies the operations in the transforms with the order that it is created.
  return (img, label)
@@ -114,8 +114,8 @@ class MyCustomDataset(Dataset):
  data = self.center_crop(data) # (2)
  data = self.to_tensor(data) # (2)
 
- # (3) Or you can call the composed version
- data = self.trasnformations(data)
+ # Or you can call the composed version
+ data = self.trasnformations(data) # (3)
 
  # Note that you only need one of the implementations, (2) or (3)
  return (img, label)