'azure', 'snow', 'silver', 'gainsboro', 'white_smoke',
]
+color_id = dict( [ (n, k) for k, n in enumerate(color_names) ] )
color_tokens = dict( [ (n, c) for n, c in zip(color_names, colors) ] )
######################################################################
def descr2img(descr, height = 6, width = 8):
if type(descr) == list:
- return torch.cat([ descr2img(d) for d in descr ], 0)
+ return torch.cat([ descr2img(d, height, width) for d in descr ], 0)
def token2color(t):
try:
######################################################################
+def descr2properties(descr, height = 6, width = 8):
+
+ if type(descr) == list:
+ return [ descr2properties(d, height, width) for d in descr ]
+
+ d = descr.split('<img>', 1)
+ d = d[-1] if len(d) > 1 else ''
+ d = d.strip().split(' ')[:height * width]
+
+ seen = {}
+ if len(d) != height * width: return []
+ for k, x in enumerate(d):
+ if x != color_names[0]:
+ if x in color_tokens:
+ if x in seen: return []
+ else:
+ return []
+ seen[x] = (color_id[x], k // width, k % width)
+
+ square_c = torch.tensor( [ x[0] for x in seen.values() ] )
+ square_i = torch.tensor( [ x[1] for x in seen.values() ] )
+ square_j = torch.tensor( [ x[2] for x in seen.values() ] )
+
+ s = all_properties(height, width, len(seen), square_i, square_j, square_c)
+
+ return s
+
+######################################################################
+
if __name__ == '__main__':
descr = generate(nb = 5)
+ print(descr2properties(descr))
with open('picoclvr_example.txt', 'w') as f:
for d in descr: