#!/usr/bin/env python
+# Any copyright is dedicated to the Public Domain.
+# https://creativecommons.org/publicdomain/zero/1.0/
+
+# Written by Francois Fleuret <francois@fleuret.org>
+
import torch, torchvision
colors = [
'black',
]
+large_colors = [
+ [ 128, 0, 0 ], [ 139, 0, 0 ], [ 165, 42, 42 ], [ 178, 34, 34 ], [ 220, 20, 60 ],
+ [ 255, 0, 0 ], [ 255, 99, 71 ], [ 255, 127, 80 ], [ 205, 92, 92 ], [ 240, 128, 128 ],
+ [ 233, 150, 122 ], [ 250, 128, 114 ], [ 255, 160, 122 ], [ 255, 69, 0 ], [ 255, 140, 0 ],
+ [ 255, 165, 0 ], [ 255, 215, 0 ], [ 184, 134, 11 ], [ 218, 165, 32 ], [ 238, 232, 170 ],
+ [ 189, 183, 107 ], [ 240, 230, 140 ], [ 128, 128, 0 ], [ 255, 255, 0 ], [ 154, 205, 50 ],
+ [ 85, 107, 47 ], [ 107, 142, 35 ], [ 124, 252, 0 ], [ 127, 255, 0 ], [ 173, 255, 47 ],
+ [ 0, 100, 0 ], [ 0, 128, 0 ], [ 34, 139, 34 ], [ 0, 255, 0 ], [ 50, 205, 50 ],
+ [ 144, 238, 144 ], [ 152, 251, 152 ], [ 143, 188, 143 ], [ 0, 250, 154 ], [ 0, 255, 127 ],
+ [ 46, 139, 87 ], [ 102, 205, 170 ], [ 60, 179, 113 ], [ 32, 178, 170 ], [ 47, 79, 79 ],
+ [ 0, 128, 128 ], [ 0, 139, 139 ], [ 0, 255, 255 ], [ 0, 255, 255 ], [ 224, 255, 255 ],
+ [ 0, 206, 209 ], [ 64, 224, 208 ], [ 72, 209, 204 ], [ 175, 238, 238 ], [ 127, 255, 212 ],
+ [ 176, 224, 230 ], [ 95, 158, 160 ], [ 70, 130, 180 ], [ 100, 149, 237 ], [ 0, 191, 255 ],
+ [ 30, 144, 255 ], [ 173, 216, 230 ], [ 135, 206, 235 ], [ 135, 206, 250 ], [ 25, 25, 112 ],
+ [ 0, 0, 128 ], [ 0, 0, 139 ], [ 0, 0, 205 ], [ 0, 0, 255 ], [ 65, 105, 225 ],
+ [ 138, 43, 226 ], [ 75, 0, 130 ], [ 72, 61, 139 ], [ 106, 90, 205 ], [ 123, 104, 238 ],
+ [ 147, 112, 219 ], [ 139, 0, 139 ], [ 148, 0, 211 ], [ 153, 50, 204 ], [ 186, 85, 211 ],
+ [ 128, 0, 128 ], [ 216, 191, 216 ], [ 221, 160, 221 ], [ 238, 130, 238 ], [ 255, 0, 255 ],
+ [ 218, 112, 214 ], [ 199, 21, 133 ], [ 219, 112, 147 ], [ 255, 20, 147 ], [ 255, 105, 180 ],
+ [ 255, 182, 193 ], [ 255, 192, 203 ], [ 250, 235, 215 ], [ 245, 245, 220 ], [ 255, 228, 196 ],
+ [ 255, 235, 205 ], [ 245, 222, 179 ], [ 255, 248, 220 ], [ 255, 250, 205 ], [ 250, 250, 210 ],
+ [ 255, 255, 224 ], [ 139, 69, 19 ], [ 160, 82, 45 ], [ 210, 105, 30 ], [ 205, 133, 63 ],
+ [ 244, 164, 96 ], [ 222, 184, 135 ], [ 210, 180, 140 ], [ 188, 143, 143 ], [ 255, 228, 181 ],
+ [ 255, 222, 173 ], [ 255, 218, 185 ], [ 255, 228, 225 ], [ 255, 240, 245 ], [ 250, 240, 230 ],
+ [ 253, 245, 230 ], [ 255, 239, 213 ], [ 255, 245, 238 ], [ 245, 255, 250 ], [ 112, 128, 144 ],
+ [ 119, 136, 153 ], [ 176, 196, 222 ], [ 230, 230, 250 ], [ 255, 250, 240 ], [ 240, 248, 255 ],
+ [ 248, 248, 255 ], [ 240, 255, 240 ], [ 255, 255, 240 ], [ 240, 255, 255 ], [ 255, 250, 250 ],
+ [ 192, 192, 192 ], [ 220, 220, 220 ], [ 245, 245, 245 ],
+]
+
+large_color_names = [
+ 'maroon', 'dark_red', 'brown', 'firebrick', 'crimson',
+ 'red', 'tomato', 'coral', 'indian_red', 'light_coral',
+ 'dark_salmon', 'salmon', 'light_salmon', 'orange_red', 'dark_orange',
+ 'orange', 'gold', 'dark_golden_rod', 'golden_rod', 'pale_golden_rod',
+ 'dark_khaki', 'khaki', 'olive', 'yellow', 'yellow_green',
+ 'dark_olive_green', 'olive_drab', 'lawn_green', 'chartreuse', 'green_yellow',
+ 'dark_green', 'green', 'forest_green', 'lime', 'lime_green',
+ 'light_green', 'pale_green', 'dark_sea_green', 'medium_spring_green', 'spring_green',
+ 'sea_green', 'medium_aqua_marine', 'medium_sea_green', 'light_sea_green', 'dark_slate_gray',
+ 'teal', 'dark_cyan', 'aqua', 'cyan', 'light_cyan',
+ 'dark_turquoise', 'turquoise', 'medium_turquoise', 'pale_turquoise', 'aqua_marine',
+ 'powder_blue', 'cadet_blue', 'steel_blue', 'corn_flower_blue', 'deep_sky_blue',
+ 'dodger_blue', 'light_blue', 'sky_blue', 'light_sky_blue', 'midnight_blue',
+ 'navy', 'dark_blue', 'medium_blue', 'blue', 'royal_blue',
+ 'blue_violet', 'indigo', 'dark_slate_blue', 'slate_blue', 'medium_slate_blue',
+ 'medium_purple', 'dark_magenta', 'dark_violet', 'dark_orchid', 'medium_orchid',
+ 'purple', 'thistle', 'plum', 'violet', 'magenta',
+ 'orchid', 'medium_violet_red', 'pale_violet_red', 'deep_pink', 'hot_pink',
+ 'light_pink', 'pink', 'antique_white', 'beige', 'bisque',
+ 'blanched_almond', 'wheat', 'corn_silk', 'lemon_chiffon', 'light_golden_rod_yellow',
+ 'light_yellow', 'saddle_brown', 'sienna', 'chocolate', 'peru',
+ 'sandy_brown', 'burly_wood', 'tan', 'rosy_brown', 'moccasin',
+ 'navajo_white', 'peach_puff', 'misty_rose', 'lavender_blush', 'linen',
+ 'old_lace', 'papaya_whip', 'sea_shell', 'mint_cream', 'slate_gray',
+ 'light_slate_gray', 'light_steel_blue', 'lavender', 'floral_white', 'alice_blue',
+ 'ghost_white', 'honeydew', 'ivory', 'azure', 'snow',
+ 'silver', 'gainsboro', 'white_smoke',
+]
+
color_tokens = dict( [ (n, c) for n, c in zip(color_names, colors) ] )
+######################################################################
+
def generate(nb, height = 6, width = 8, max_nb_statements = 10):
descr = [ ]
for n in range(nb):
- nb = torch.randint(5, (1,)) + 1
- shape_position = torch.randperm(height * width)[:nb]
- shape_c = torch.randperm(5)[:nb] + 1
- shape_i = shape_position.div(width, rounding_mode = 'floor')
- shape_j = shape_position % width
+
+ nb_squares = torch.randint(len(color_tokens) - 1, (1,)) + 1
+ square_position = torch.randperm(height * width)[:nb_squares]
+ square_c = torch.randperm(len(color_tokens) - 1)[:nb_squares] + 1
+ square_i = square_position.div(width, rounding_mode = 'floor')
+ square_j = square_position % width
img = [ 0 ] * height * width
- for k in range(nb): img[shape_position[k]] = shape_c[k]
+ for k in range(nb_squares): img[square_position[k]] = square_c[k]
+
+ # generates all the true relations
s = [ ]
- for r, c in [ (k, color_names[shape_c[k]]) for k in range(nb) ]:
+ for r, c in [ (k, color_names[square_c[k]]) for k in range(nb_squares) ]:
s += [ f'there is {c}' ]
- if shape_i[r] >= height - height/4: s += [ f'{c} bottom' ]
- if shape_i[r] < height/4: s += [ f'{c} top' ]
- if shape_j[r] >= width - width/4: s += [ f'{c} right' ]
- if shape_j[r] < width/4: s += [ f'{c} left' ]
+ 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}' ]
- for t, d in [ (k, color_names[shape_c[k]]) for k in range(nb) ]:
- if shape_i[r] > shape_i[t]: s += [ f'{c} below {d}' ]
- if shape_i[r] < shape_i[t]: s += [ f'{c} above {d}' ]
- if shape_j[r] > shape_j[t]: s += [ f'{c} right of {d}' ]
- if shape_j[r] < shape_j[t]: s += [ f'{c} left of {d}' ]
+ # pick at most max_nb_statements at random
nb_statements = torch.randint(max_nb_statements, (1,)) + 1
s = ' <sep> '.join([ s[k] for k in torch.randperm(len(s))[:nb_statements] ] )
s += ' <img> ' + ' '.join([ f'{color_names[n]}' for n in img ])
+
descr += [ s ]
return descr
if __name__ == '__main__':
descr = generate(5)
+ for d in descr:
+ print(d)
+ print()
+
img = descr2img(descr)
- print(descr, img.size())
+ print(img.size())
+
torchvision.utils.save_image(img / 255.,
- 'example.png', nrow = 16, pad_value = 0.8)
+ 'picoclvr_example.png', nrow = 16, pad_value = 0.8)
import time
projects / mygpt.git / blobdiff