Update for PPM format (keras-team#7750)

Author: nzw0301

docs/templates/preprocessing/image.md

@@ -86,7 +86,7 @@ Generate batches of tensor image data with real-time data augmentation. The data
     - __flow_from_directory(directory)__: Takes the path to a directory, and generates batches of augmented/normalized data. Yields batches indefinitely, in an infinite loop.
         - __Arguments__:
             - __directory__: path to the target directory. It should contain one subdirectory per class.
-                Any PNG, JPG or BMP images inside each of the subdirectories directory tree will be included in the generator.
+                Any PNG, JPG, BMP or PPM images inside each of the subdirectories directory tree will be included in the generator.
                 See [this script](https://gist.github.com/fchollet/0830affa1f7f19fd47b06d4cf89ed44d) for more details.
             - __target_size__: tuple of integers `(height, width)`, default: `(256, 256)`. 
                 The dimensions to which all images found will be resized.

keras/preprocessing/image.py

@@ -333,7 +333,7 @@ def load_img(path, grayscale=False, target_size=None):
     return img
 
 
-def list_pictures(directory, ext='jpg|jpeg|bmp|png'):
+def list_pictures(directory, ext='jpg|jpeg|bmp|png|ppm'):
     return [os.path.join(root, f)
             for root, _, files in os.walk(directory) for f in files
             if re.match(r'([\w]+\.(?:' + ext + '))', f)]