added examples for other weights, pascal_voc works too

.gitignore

@@ -1,4 +1,7 @@
 *.npy
 *.pyc
 *.png
-
+*.caffemodel
+*.prototxt
+*.h5
+*.json

README.md

@@ -17,21 +17,30 @@ Already converted weights can be downloaded here:
 [pspnet101_cityscapes.npy](https://www.dropbox.com/s/b21j6hi6qql90l0/pspnet101_cityscapes.npy?dl=0)
 [pspnet101_voc2012.npy](https://www.dropbox.com/s/xkjmghsbn6sfj9k/pspnet101_voc2012.npy?dl=0)
 
-weights should be placed in the directory with pspnet.py
+npy weights should be placed in the directory weights/npy.
 
 The interpolation layer is implemented as custom layer "Interp"
 
 ## Important
 
 Results Keras:
-![Original](test.jpg)
+![Original](example_images/ade20k.jpg)
+![New](example_results/ade20k_seg.jpg)
+![New](example_results/ade20k_seg_blended.jpg)
+![New](example_results/ade20k_probs.jpg)
 
-![New](test_seg.jpg)
-![New](test_seg_blended.jpg)
-![New](test_probs.jpg)
+![Original](example_images/cityscapes.png)
+![New](example_results/cityscapes_seg.jpg)
+![New](example_results/cityscapes_seg_blended.jpg)
+![New](example_results/cityscapes_probs.jpg)
+
+![Original](example_images/pascal_voc.jpg)
+![New](example_results/pascal_voc_seg.jpg)
+![New](example_results/pascal_voc_seg_blended.jpg)
+![New](example_results/pascal_voc_probs.jpg)
 
 ## Pycaffe result
-![Pycaffe results](test_pycaffe.jpg)
+![Pycaffe results](example_results/ade20k_seg_pycaffe.jpg)
 ## Dependencies:
 1. Tensorflow
 2. Keras
@@ -42,5 +51,7 @@ Results Keras:
 ## Usage:
 
 ```bash
-python pspnet.py --input-path INPUT_PATH --output-path OUTPUT_PATH
+python pspnet.py
+python pspnet.py -m pspnet101_cityscapes -i example_images/cityscapes.png -o example_results/cityscapes.jpg
+python pspnet.py -m pspnet101_voc2012 -i example_images/pascal_voc.jpg -o example_results/pascal_voc.jpg
 ```

pspnet.py

@@ -1,6 +1,7 @@
+#!/usr/bin/env python
 from __future__ import print_function
 import os
-from os.path import splitext
+from os.path import splitext, join
 import argparse
 import numpy as np
 from scipy import misc, ndimage
@@ -19,8 +20,8 @@ class PSPNet(object):
 
     def __init__(self, nb_classes, resnet_layers, input_shape, weights):
         self.input_shape = input_shape
-        json_path = weights + ".json"
-        h5_path = weights + ".h5"
+        json_path = join("weights", "keras", weights + ".json")
+        h5_path = join("weights", "keras", weights + ".h5")
         if os.path.isfile(json_path) and os.path.isfile(h5_path):
             print("Keras model & weights found, loading...")
             with open(json_path, 'r') as file_handle:
@@ -67,9 +68,9 @@ class PSPNet(object):
         return pred[0]
 
     def set_npy_weights(self, weights_path):
-        npy_weights_path = weights_path + ".npy"
-        json_path = weights_path + ".json"
-        h5_path = weights_path + ".h5"
+        npy_weights_path = join("weights", "npy", weights_path + ".npy")
+        json_path = join("weights", "keras", weights_path + ".json")
+        h5_path = join("weights", "keras", weights_path + ".h5")
 
         print("Importing weights from %s" % npy_weights_path)
         weights = np.load(npy_weights_path).item()
@@ -126,9 +127,9 @@ if __name__ == "__main__":
                         choices=['pspnet50_ade20k',
                                  'pspnet101_cityscapes',
                                  'pspnet101_voc2012'])
-    parser.add_argument('-i', '--input_path', type=str, default='test.jpg',
+    parser.add_argument('-i', '--input_path', type=str, default='example_images/ade20k.jpg',
                         help='Path the input image')
-    parser.add_argument('-o', '--output_path', type=str, default='test.jpg',
+    parser.add_argument('-o', '--output_path', type=str, default='example_results/ade20k.jpg',
                         help='Path to output')
     parser.add_argument('--id', default="0")
     args = parser.parse_args()

weight_converter.py

@@ -1,3 +1,5 @@
+#!/usr/bin/env python
+
 from __future__ import print_function
 
 import sys