######################################################################
+def all_properties(height, width, nb_squares, square_i, square_j, square_c):
+ s = [ ]
+
+ for r, c in [ (k, color_names[square_c[k]]) for k in range(nb_squares) ]:
+ s += [ f'there is {c}' ]
+
+ if square_i[r] >= height - height//3: s += [ f'{c} bottom' ]
+ if square_i[r] < height//3: s += [ f'{c} top' ]
+ if square_j[r] >= width - width//3: s += [ f'{c} right' ]
+ if square_j[r] < width//3: s += [ f'{c} left' ]
+
+ for t, d in [ (k, color_names[square_c[k]]) for k in range(nb_squares) ]:
+ if square_i[r] > square_i[t]: s += [ f'{c} below {d}' ]
+ if square_i[r] < square_i[t]: s += [ f'{c} above {d}' ]
+ if square_j[r] > square_j[t]: s += [ f'{c} right of {d}' ]
+ if square_j[r] < square_j[t]: s += [ f'{c} left of {d}' ]
+
+ return s
+
+######################################################################
+
def generate(nb, height = 6, width = 8,
max_nb_squares = 5, max_nb_statements = 10,
many_colors = False):
# generates all the true relations
- s = [ ]
-
- for r, c in [ (k, color_names[square_c[k]]) for k in range(nb_squares) ]:
- s += [ f'there is {c}' ]
-
- if square_i[r] >= height - height//3: s += [ f'{c} bottom' ]
- if square_i[r] < height//3: s += [ f'{c} top' ]
- if square_j[r] >= width - width//3: s += [ f'{c} right' ]
- if square_j[r] < width//3: s += [ f'{c} left' ]
-
- for t, d in [ (k, color_names[square_c[k]]) for k in range(nb_squares) ]:
- if square_i[r] > square_i[t]: s += [ f'{c} below {d}' ]
- if square_i[r] < square_i[t]: s += [ f'{c} above {d}' ]
- if square_j[r] > square_j[t]: s += [ f'{c} right of {d}' ]
- if square_j[r] < square_j[t]: s += [ f'{c} left of {d}' ]
+ s = all_properties(height, width, nb_squares, square_i, square_j, square_c)
# pick at most max_nb_statements at random
if __name__ == '__main__':
descr = generate(nb = 5)
- for d in descr:
- print(d)
- print()
- img = descr2img(descr)
- print(img.size())
+ with open('picoclvr_example.txt', 'w') as f:
+ for d in descr:
+ f.write(f'{d}\n\n')
+ img = descr2img(descr)
torchvision.utils.save_image(img / 255.,
'picoclvr_example.png', nrow = 16, pad_value = 0.8)