X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?p=flatland.git;a=blobdiff_plain;f=flatland-test.py;h=2c269ba0eb9dcc35dcb15ef7ca6df2bc9e0fddc3;hp=1f92fa3ae2f7e9c848beaf8b123d262cfc5b87c8;hb=924ef5308c54784d2c0a9bbd282e55a16efbf318;hpb=dc147618a2d9b65027b751b5e1306241a2221668

diff --git a/flatland-test.py b/flatland-test.py
index 1f92fa3..2c269ba 100755
--- a/flatland-test.py
+++ b/flatland-test.py
@@ -1,4 +1,4 @@
-#!/usr/bin/env python-for-pytorch
+#!/usr/bin/env python
 
 #
 #  flatland is a simple 2d physical simulator
@@ -25,7 +25,7 @@ import torch
 import torchvision
 import argparse
 
-from _ext import flatland
+import flatland
 
 ######################################################################
 
@@ -47,19 +47,19 @@ parser.add_argument('--height',
                     help = 'Image height')
 
 parser.add_argument('--nb_shapes',
-                    type = int, default = 10,
+                    type = int, default = 8,
                     help = 'Image height')
 
 parser.add_argument('--nb_sequences',
-                    type = int, default = 1,
+                    type = int, default = 8,
                     help = 'How many sequences to generate')
 
 parser.add_argument('--nb_images_per_sequences',
-                    type = int, default = 3,
+                    type = int, default = 16,
                     help = 'How many images per sequence')
 
 parser.add_argument('--randomize_colors',
-                    action='store_true', default=False,
+                    action='store_true', default=True,
                     help = 'Should the shapes be of different colors')
 
 parser.add_argument('--randomize_shape_size',
@@ -110,8 +110,8 @@ x = flatland.generate_sequence(False,
                                args.nb_images_per_sequences,
                                args.height, args.width,
                                args.nb_shapes,
-                               args.randomize_colors,
-                               args.randomize_shape_size)
+                               args.randomize_shape_size,
+                               args.randomize_colors)
 
 sequences_to_image(x, gap = 3, gap_color = (0, 150, 200)).save('sequences.png')