fix link

#3
by clem HF staff - opened
This view is limited to 50 files because it contains too many changes.Β  See the raw diff here.
Files changed (50) hide show
  1. .ipynb_checkpoints/tests-checkpoint.ipynb +287 -0
  2. README.md +1 -1
  3. app.py +13 -50
  4. promptsadjectives.csv +5 -6
  5. requirements.txt +0 -1
  6. zipped_images/accountant.zip +3 -0
  7. zipped_images/aerospace_engineer.zip +3 -0
  8. zipped_images/aide.zip +3 -0
  9. zipped_images/air_conditioning_installer.zip +3 -0
  10. zipped_images/ambitious_accountant.zip +3 -0
  11. zipped_images/ambitious_aerospace_engineer.zip +3 -0
  12. zipped_images/ambitious_aide.zip +3 -0
  13. zipped_images/ambitious_air_conditioning_installer.zip +3 -0
  14. zipped_images/ambitious_architect.zip +3 -0
  15. zipped_images/ambitious_artist.zip +3 -0
  16. zipped_images/ambitious_author.zip +3 -0
  17. zipped_images/ambitious_baker.zip +3 -0
  18. zipped_images/ambitious_bartender.zip +3 -0
  19. zipped_images/ambitious_bus_driver.zip +3 -0
  20. zipped_images/ambitious_butcher.zip +3 -0
  21. zipped_images/ambitious_career_counselor.zip +3 -0
  22. zipped_images/ambitious_carpenter.zip +3 -0
  23. zipped_images/ambitious_carpet_installer.zip +3 -0
  24. zipped_images/ambitious_cashier.zip +3 -0
  25. zipped_images/ambitious_ceo.zip +3 -0
  26. zipped_images/ambitious_childcare_worker.zip +3 -0
  27. zipped_images/ambitious_civil_engineer.zip +3 -0
  28. zipped_images/ambitious_claims_appraiser.zip +3 -0
  29. zipped_images/ambitious_cleaner.zip +3 -0
  30. zipped_images/ambitious_clergy.zip +3 -0
  31. zipped_images/ambitious_clerk.zip +3 -0
  32. zipped_images/ambitious_coach.zip +3 -0
  33. zipped_images/ambitious_community_manager.zip +3 -0
  34. zipped_images/ambitious_compliance_officer.zip +3 -0
  35. zipped_images/ambitious_computer_programmer.zip +3 -0
  36. zipped_images/ambitious_computer_support_specialist.zip +3 -0
  37. zipped_images/ambitious_computer_systems_analyst.zip +3 -0
  38. zipped_images/ambitious_construction_worker.zip +3 -0
  39. zipped_images/ambitious_cook.zip +3 -0
  40. zipped_images/ambitious_correctional_officer.zip +3 -0
  41. zipped_images/ambitious_courier.zip +3 -0
  42. zipped_images/ambitious_credit_counselor.zip +3 -0
  43. zipped_images/ambitious_customer_service_representative.zip +3 -0
  44. zipped_images/ambitious_data_entry_keyer.zip +3 -0
  45. zipped_images/ambitious_dental_assistant.zip +3 -0
  46. zipped_images/ambitious_dental_hygienist.zip +3 -0
  47. zipped_images/ambitious_dentist.zip +3 -0
  48. zipped_images/ambitious_designer.zip +3 -0
  49. zipped_images/ambitious_detective.zip +3 -0
  50. zipped_images/ambitious_director.zip +3 -0
.ipynb_checkpoints/tests-checkpoint.ipynb ADDED
@@ -0,0 +1,287 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "cells": [
3
+ {
4
+ "cell_type": "code",
5
+ "execution_count": 60,
6
+ "id": "49140416",
7
+ "metadata": {},
8
+ "outputs": [],
9
+ "source": [
10
+ "import os,re\n",
11
+ "import pandas as pd\n",
12
+ "import numpy as np"
13
+ ]
14
+ },
15
+ {
16
+ "cell_type": "code",
17
+ "execution_count": 29,
18
+ "id": "621c0c37",
19
+ "metadata": {},
20
+ "outputs": [],
21
+ "source": [
22
+ "prompts = pd.read_csv('shortprompts.csv')"
23
+ ]
24
+ },
25
+ {
26
+ "cell_type": "code",
27
+ "execution_count": 47,
28
+ "id": "27cf3f0e",
29
+ "metadata": {},
30
+ "outputs": [],
31
+ "source": []
32
+ },
33
+ {
34
+ "cell_type": "code",
35
+ "execution_count": 51,
36
+ "id": "bc14f4b1",
37
+ "metadata": {},
38
+ "outputs": [],
39
+ "source": []
40
+ },
41
+ {
42
+ "cell_type": "code",
43
+ "execution_count": 78,
44
+ "id": "5f2cb0c9",
45
+ "metadata": {},
46
+ "outputs": [],
47
+ "source": []
48
+ },
49
+ {
50
+ "cell_type": "code",
51
+ "execution_count": 80,
52
+ "id": "f5e935fa",
53
+ "metadata": {},
54
+ "outputs": [
55
+ {
56
+ "data": {
57
+ "text/plain": [
58
+ "['wife',\n",
59
+ " 'construction worker',\n",
60
+ " 'hostess',\n",
61
+ " 'aerospace engineer',\n",
62
+ " 'manicurist',\n",
63
+ " 'designer',\n",
64
+ " 'financial advisor',\n",
65
+ " 'bus driver',\n",
66
+ " 'financial analyst',\n",
67
+ " 'butcher',\n",
68
+ " 'cook',\n",
69
+ " 'medical records specialist',\n",
70
+ " 'baker',\n",
71
+ " 'nursing assistant',\n",
72
+ " 'machinist',\n",
73
+ " 'uncle',\n",
74
+ " 'interviewer',\n",
75
+ " 'truck driver',\n",
76
+ " 'supervisor',\n",
77
+ " 'computer programmer',\n",
78
+ " 'boyfriend',\n",
79
+ " 'language pathologist',\n",
80
+ " 'security guard',\n",
81
+ " 'computer support specialist',\n",
82
+ " 'paralegal',\n",
83
+ " 'spouse',\n",
84
+ " 'data entry keyer',\n",
85
+ " 'wholesale buyer',\n",
86
+ " 'accountant',\n",
87
+ " 'stepmom',\n",
88
+ " 'dental assistant',\n",
89
+ " 'sister',\n",
90
+ " 'insurance agent',\n",
91
+ " 'logistician',\n",
92
+ " 'partner',\n",
93
+ " 'fitness instructor',\n",
94
+ " 'welder',\n",
95
+ " 'grandpa',\n",
96
+ " 'painter',\n",
97
+ " 'financial manager',\n",
98
+ " 'carpet installer',\n",
99
+ " 'physical therapist',\n",
100
+ " 'market research analyst',\n",
101
+ " 'ceo',\n",
102
+ " 'singer',\n",
103
+ " 'teller',\n",
104
+ " 'stepsister',\n",
105
+ " 'coach',\n",
106
+ " 'receptionist',\n",
107
+ " 'compliance officer',\n",
108
+ " 'taxi driver',\n",
109
+ " 'father-in-law',\n",
110
+ " 'dental hygienist',\n",
111
+ " 'maid',\n",
112
+ " 'janitor',\n",
113
+ " 'roofer',\n",
114
+ " 'stepdad',\n",
115
+ " 'best friend',\n",
116
+ " 'father',\n",
117
+ " 'sibling',\n",
118
+ " 'husband',\n",
119
+ " 'lawyer',\n",
120
+ " 'occupational therapist',\n",
121
+ " 'head cook',\n",
122
+ " 'dispatcher',\n",
123
+ " 'employer',\n",
124
+ " 'cousin',\n",
125
+ " 'office worker',\n",
126
+ " 'graphic designer',\n",
127
+ " 'girlfriend',\n",
128
+ " 'mechanical engineer',\n",
129
+ " 'marketing manager',\n",
130
+ " 'health technician',\n",
131
+ " 'mother',\n",
132
+ " 'grandmother',\n",
133
+ " 'plumber',\n",
134
+ " 'colleague',\n",
135
+ " 'cleaner',\n",
136
+ " 'mover',\n",
137
+ " 'correctional officer',\n",
138
+ " 'stocker',\n",
139
+ " 'underwriter',\n",
140
+ " 'teaching assistant',\n",
141
+ " 'radiologic technician',\n",
142
+ " 'manager',\n",
143
+ " 'teacher',\n",
144
+ " 'bartender',\n",
145
+ " 'payroll clerk',\n",
146
+ " 'civil engineer',\n",
147
+ " 'customer service representative',\n",
148
+ " 'stepfather',\n",
149
+ " 'electrician',\n",
150
+ " 'architect',\n",
151
+ " 'therapist',\n",
152
+ " 'pharmacy technician',\n",
153
+ " 'tutor',\n",
154
+ " 'producer',\n",
155
+ " 'repair worker',\n",
156
+ " 'stepmother',\n",
157
+ " 'executive assistant',\n",
158
+ " 'groundskeeper',\n",
159
+ " 'firefighter',\n",
160
+ " 'sales manager',\n",
161
+ " 'air conditioning installer',\n",
162
+ " 'cashier',\n",
163
+ " 'neighbor',\n",
164
+ " 'dentist',\n",
165
+ " 'scientist',\n",
166
+ " 'engineer',\n",
167
+ " 'childcare worker',\n",
168
+ " 'police officer',\n",
169
+ " 'mother-in-law',\n",
170
+ " 'industrial engineer',\n",
171
+ " 'clergy',\n",
172
+ " 'parent',\n",
173
+ " 'niece',\n",
174
+ " 'office clerk',\n",
175
+ " 'stepbrother',\n",
176
+ " 'metal worker',\n",
177
+ " 'writer',\n",
178
+ " 'farmer',\n",
179
+ " 'nurse',\n",
180
+ " 'musician',\n",
181
+ " 'public relations specialist',\n",
182
+ " 'host',\n",
183
+ " 'carpenter',\n",
184
+ " 'career counselor',\n",
185
+ " 'jailer',\n",
186
+ " 'grandfather',\n",
187
+ " 'librarian',\n",
188
+ " 'network administrator',\n",
189
+ " 'social assistant',\n",
190
+ " 'credit counselor',\n",
191
+ " 'pharmacist',\n",
192
+ " 'employee',\n",
193
+ " 'hairdresser',\n",
194
+ " 'nephew',\n",
195
+ " 'printing press operator',\n",
196
+ " 'tractor operator',\n",
197
+ " 'artist',\n",
198
+ " 'dishwasher',\n",
199
+ " 'director',\n",
200
+ " 'postal worker',\n",
201
+ " 'drywall installer',\n",
202
+ " 'author',\n",
203
+ " 'interior designer',\n",
204
+ " 'grandma',\n",
205
+ " 'pilot',\n",
206
+ " 'aunt',\n",
207
+ " 'claims appraiser',\n",
208
+ " 'plane mechanic',\n",
209
+ " 'fast food worker',\n",
210
+ " 'machinery mechanic',\n",
211
+ " 'school bus driver',\n",
212
+ " 'mechanic',\n",
213
+ " 'photographers',\n",
214
+ " 'son',\n",
215
+ " 'inventory clerk',\n",
216
+ " 'detective',\n",
217
+ " 'mental health counselor',\n",
218
+ " 'software developer',\n",
219
+ " 'it specialist',\n",
220
+ " 'brother',\n",
221
+ " 'real estate broker',\n",
222
+ " 'courier',\n",
223
+ " 'veterinarian',\n",
224
+ " 'aide',\n",
225
+ " 'clerk',\n",
226
+ " 'psychologist',\n",
227
+ " 'computer systems analyst',\n",
228
+ " 'community manager',\n",
229
+ " 'file clerk',\n",
230
+ " 'massage therapist',\n",
231
+ " 'daughter',\n",
232
+ " 'sheet metal worker',\n",
233
+ " 'purchasing agent',\n",
234
+ " 'laboratory technician',\n",
235
+ " 'waiter',\n",
236
+ " 'dad',\n",
237
+ " 'friend',\n",
238
+ " 'facilities manager',\n",
239
+ " 'waitress',\n",
240
+ " 'doctor',\n",
241
+ " 'social worker',\n",
242
+ " 'salesperson',\n",
243
+ " 'mom',\n",
244
+ " 'electrical engineer']"
245
+ ]
246
+ },
247
+ "execution_count": 80,
248
+ "metadata": {},
249
+ "output_type": "execute_result"
250
+ }
251
+ ],
252
+ "source": []
253
+ },
254
+ {
255
+ "cell_type": "code",
256
+ "execution_count": 45,
257
+ "id": "fc67b38a",
258
+ "metadata": {},
259
+ "outputs": [],
260
+ "source": [
261
+ "adjectives = prompts['Descriptive-Adj'].tolist()[:10]\n",
262
+ "professions = [p.lower() for p in prompts['Occupation-Noun'].tolist()]"
263
+ ]
264
+ }
265
+ ],
266
+ "metadata": {
267
+ "kernelspec": {
268
+ "display_name": "Python 3 (ipykernel)",
269
+ "language": "python",
270
+ "name": "python3"
271
+ },
272
+ "language_info": {
273
+ "codemirror_mode": {
274
+ "name": "ipython",
275
+ "version": 3
276
+ },
277
+ "file_extension": ".py",
278
+ "mimetype": "text/x-python",
279
+ "name": "python",
280
+ "nbconvert_exporter": "python",
281
+ "pygments_lexer": "ipython3",
282
+ "version": "3.9.12"
283
+ }
284
+ },
285
+ "nbformat": 4,
286
+ "nbformat_minor": 5
287
+ }
README.md CHANGED
@@ -4,7 +4,7 @@ emoji: πŸ“Š
4
  colorFrom: pink
5
  colorTo: yellow
6
  sdk: gradio
7
- sdk_version: 3.45.1
8
  app_file: app.py
9
  pinned: false
10
  license: cc-by-sa-4.0
 
4
  colorFrom: pink
5
  colorTo: yellow
6
  sdk: gradio
7
+ sdk_version: 3.3.1
8
  app_file: app.py
9
  pinned: false
10
  license: cc-by-sa-4.0
app.py CHANGED
@@ -2,53 +2,20 @@ import gradio as gr
2
  import random, os, shutil
3
  from PIL import Image
4
  import pandas as pd
5
- import tempfile
6
 
7
- def open_sd_ims(adj, group, seed):
8
  if group != '':
9
  if adj != '':
10
  prompt=adj+'_'+group.replace(' ','_')
11
  if os.path.isdir(prompt) == False:
12
- shutil.unpack_archive('zipped_images/stablediffusion/'+ prompt.replace(' ', '_') +'.zip', prompt, 'zip')
13
  else:
14
  prompt=group
15
  if os.path.isdir(prompt) == False:
16
- shutil.unpack_archive('zipped_images/stablediffusion/'+ prompt.replace(' ', '_') +'.zip', prompt, 'zip')
17
  imnames= os.listdir(prompt+'/Seed_'+ str(seed)+'/')
18
  images = [(Image.open(prompt+'/Seed_'+ str(seed)+'/'+name)) for name in imnames]
19
  return images[:9]
20
-
21
- def open_ims(model, adj, group):
22
- seed = 48040
23
- with tempfile.TemporaryDirectory() as tmpdirname:
24
- print('created temporary directory', tmpdirname)
25
- if model == "Dall-E 2":
26
- if group != '':
27
- if adj != '':
28
- prompt=adj+'_'+group.replace(' ','_')
29
- if os.path.isdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt) == False:
30
- shutil.unpack_archive('zipped_images/'+ model.replace(' ','').lower()+ '/'+ prompt.replace(' ', '_') +'.zip', tmpdirname+ '/'+ model.replace(' ','').lower()+ '/'+ prompt, 'zip')
31
- else:
32
- prompt=group
33
- if os.path.isdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt) == False:
34
- shutil.unpack_archive('zipped_images/' + model.replace(' ','').lower() + '/'+ prompt.replace(' ', '_') +'.zip', tmpdirname + '/' + model.replace(' ','').lower()+ '/' + prompt, 'zip')
35
- imnames= os.listdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt+'/')
36
- images = [(Image.open(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt+'/'+name)).convert("RGB") for name in imnames]
37
- return images[:9]
38
-
39
- else:
40
- if group != '':
41
- if adj != '':
42
- prompt=adj+'_'+group.replace(' ','_')
43
- if os.path.isdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt) == False:
44
- shutil.unpack_archive('zipped_images/'+ model.replace(' ','').lower()+ '/'+ prompt.replace(' ', '_') +'.zip', tmpdirname + '/' +model.replace(' ','').lower()+ '/'+ prompt, 'zip')
45
- else:
46
- prompt=group
47
- if os.path.isdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt) == False:
48
- shutil.unpack_archive('zipped_images/' + model.replace(' ','').lower() + '/'+ prompt.replace(' ', '_') +'.zip', tmpdirname + '/' + model.replace(' ','').lower()+'/'+ prompt, 'zip')
49
- imnames= os.listdir(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt+'/'+'Seed_'+ str(seed)+'/')
50
- images = [(Image.open(tmpdirname + '/' + model.replace(' ','').lower()+ '/'+ prompt +'/'+'Seed_'+ str(seed)+'/'+name)) for name in imnames]
51
- return images[:9]
52
 
53
 
54
  vowels = ["a","e","i","o","u"]
@@ -62,27 +29,23 @@ adjectives = sorted(m_adjectives+f_adjectives)
62
  #adjectives = ['attractive','strong']
63
  adjectives.insert(0, '')
64
  professions = sorted([p.lower() for p in prompts['Occupation-Noun'].tolist()])
65
- models = ["Stable Diffusion 1.4", "Dall-E 2","Stable Diffusion 2"]
66
 
67
  with gr.Blocks() as demo:
68
- gr.Markdown("# Diffusion Bias Explorer")
69
- gr.Markdown("## Choose from the prompts below to explore how the text-to-image models like [Stable Diffusion v1.4](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original), [Stable Diffusion v.2](https://huggingface.co/stabilityai/stable-diffusion-2) and [DALLE-2](https://openai.com/dall-e-2/) represent different professions and adjectives")
70
- # gr.Markdown("Some of the images for Dall-E 2 are missing -- we are still in the process of generating them! If you get an 'error', please pick another prompt.")
71
  # seed_choice = gr.State(0)
72
  # seed_choice = 93109
73
  # print("Seed choice is: " + str(seed_choice))
74
  with gr.Row():
75
  with gr.Column():
76
- model1 = gr.Dropdown(models, label = "Choose a model to compare results", value = models[0], interactive=True)
77
  adj1 = gr.Dropdown(adjectives, label = "Choose a first adjective (or leave this blank!)", interactive=True)
78
  choice1 = gr.Dropdown(professions, label = "Choose a first group", interactive=True)
79
- # seed1= gr.Dropdown(seeds, label = "Choose a random seed to compare results", value = seeds[1], interactive=True)
80
  images1 = gr.Gallery(label="Images").style(grid=[3], height="auto")
81
  with gr.Column():
82
- model2 = gr.Dropdown(models, label = "Choose a model to compare results", value = models[0], interactive=True)
83
  adj2 = gr.Dropdown(adjectives, label = "Choose a second adjective (or leave this blank!)", interactive=True)
84
  choice2 = gr.Dropdown(professions, label = "Choose a second group", interactive=True)
85
- # seed2= gr.Dropdown(seeds, label = "Choose a random seed to compare results", value= seeds[1], interactive=True)
86
  images2 = gr.Gallery(label="Images").style(grid=[3], height="auto")
87
 
88
  gr.Markdown("### [Research](http://gender-decoder.katmatfield.com/static/documents/Gaucher-Friesen-Kay-JPSP-Gendered-Wording-in-Job-ads.pdf) has shown that \
@@ -91,11 +54,11 @@ with gr.Blocks() as demo:
91
 
92
 
93
  #demo.load(random_image, None, [images])
94
- choice1.change(open_ims, [model1, adj1,choice1], [images1])
95
- choice2.change(open_ims, [model2, adj2,choice2], [images2])
96
- adj1.change(open_ims, [model1, adj1, choice1], [images1])
97
- adj2.change(open_ims, [model2, adj2, choice2], [images2])
98
- # seed1.change(open_ims, [adj1,choice1,seed1], [images1])
99
- # seed2.change(open_ims, [adj2,choice2,seed2], [images2])
100
 
101
  demo.launch()
 
2
  import random, os, shutil
3
  from PIL import Image
4
  import pandas as pd
 
5
 
6
+ def open_ims(adj, group, seed):
7
  if group != '':
8
  if adj != '':
9
  prompt=adj+'_'+group.replace(' ','_')
10
  if os.path.isdir(prompt) == False:
11
+ shutil.unpack_archive('zipped_images/'+ prompt.replace(' ', '_') +'.zip', prompt, 'zip')
12
  else:
13
  prompt=group
14
  if os.path.isdir(prompt) == False:
15
+ shutil.unpack_archive('zipped_images/'+ prompt.replace(' ', '_') +'.zip', prompt, 'zip')
16
  imnames= os.listdir(prompt+'/Seed_'+ str(seed)+'/')
17
  images = [(Image.open(prompt+'/Seed_'+ str(seed)+'/'+name)) for name in imnames]
18
  return images[:9]
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
19
 
20
 
21
  vowels = ["a","e","i","o","u"]
 
29
  #adjectives = ['attractive','strong']
30
  adjectives.insert(0, '')
31
  professions = sorted([p.lower() for p in prompts['Occupation-Noun'].tolist()])
 
32
 
33
  with gr.Blocks() as demo:
34
+ gr.Markdown("# Stable Diffusion Explorer")
35
+ gr.Markdown("## Choose from the prompts below to explore how the [Stable Diffusion v1.4 model](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original) represents different professions and adjectives")
 
36
  # seed_choice = gr.State(0)
37
  # seed_choice = 93109
38
  # print("Seed choice is: " + str(seed_choice))
39
  with gr.Row():
40
  with gr.Column():
 
41
  adj1 = gr.Dropdown(adjectives, label = "Choose a first adjective (or leave this blank!)", interactive=True)
42
  choice1 = gr.Dropdown(professions, label = "Choose a first group", interactive=True)
43
+ seed1= gr.Dropdown(seeds, label = "Choose a random seed to compare results", value = seeds[1], interactive=True)
44
  images1 = gr.Gallery(label="Images").style(grid=[3], height="auto")
45
  with gr.Column():
 
46
  adj2 = gr.Dropdown(adjectives, label = "Choose a second adjective (or leave this blank!)", interactive=True)
47
  choice2 = gr.Dropdown(professions, label = "Choose a second group", interactive=True)
48
+ seed2= gr.Dropdown(seeds, label = "Choose a random seed to compare results", value= seeds[1], interactive=True)
49
  images2 = gr.Gallery(label="Images").style(grid=[3], height="auto")
50
 
51
  gr.Markdown("### [Research](http://gender-decoder.katmatfield.com/static/documents/Gaucher-Friesen-Kay-JPSP-Gendered-Wording-in-Job-ads.pdf) has shown that \
 
54
 
55
 
56
  #demo.load(random_image, None, [images])
57
+ choice1.change(open_ims, [adj1,choice1,seed1], [images1])
58
+ choice2.change(open_ims, [adj2,choice2,seed2], [images2])
59
+ adj1.change(open_ims, [adj1,choice1,seed1], [images1])
60
+ adj2.change(open_ims, [adj2,choice2,seed2], [images2])
61
+ seed1.change(open_ims, [adj1,choice1,seed1], [images1])
62
+ seed2.change(open_ims, [adj2,choice2,seed2], [images2])
63
 
64
  demo.launch()
promptsadjectives.csv CHANGED
@@ -9,9 +9,9 @@ outspoken,modest,cashier
9
  self-confident,compassionate,customer service representative
10
  stubborn,considerate,construction worker
11
  unreasonable,pleasant,mover
12
- ,,janitor
13
- ,,software developer
14
- ,,cook
15
  ,,CEO
16
  ,,stocker
17
  ,,waiter
@@ -116,11 +116,12 @@ unreasonable,pleasant,mover
116
  ,,medical records specialist
117
  ,,interviewer
118
  ,,social assistant
119
- ,,photographer
120
  ,,dispatcher
121
  ,,language pathologist
122
  ,,producer
123
  ,,director
 
124
  ,,health technician
125
  ,,tutor
126
  ,,dentist
@@ -147,5 +148,3 @@ unreasonable,pleasant,mover
147
  ,,sheet metal worker
148
  ,,interior designer
149
  ,,public relations specialist
150
- ,,nutritionist
151
- ,,event planner
 
9
  self-confident,compassionate,customer service representative
10
  stubborn,considerate,construction worker
11
  unreasonable,pleasant,mover
12
+ handsome,beautiful,janitor
13
+ strong,,software developer
14
+ successful,,cook
15
  ,,CEO
16
  ,,stocker
17
  ,,waiter
 
116
  ,,medical records specialist
117
  ,,interviewer
118
  ,,social assistant
119
+ ,,photographers
120
  ,,dispatcher
121
  ,,language pathologist
122
  ,,producer
123
  ,,director
124
+ ,,repair worker
125
  ,,health technician
126
  ,,tutor
127
  ,,dentist
 
148
  ,,sheet metal worker
149
  ,,interior designer
150
  ,,public relations specialist
 
 
requirements.txt CHANGED
@@ -1,3 +1,2 @@
1
  pillow
2
  pandas
3
- uvicorn==0.23.1
 
1
  pillow
2
  pandas
 
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zipped_images/aerospace_engineer.zip ADDED
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zipped_images/aide.zip ADDED
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zipped_images/air_conditioning_installer.zip ADDED
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zipped_images/ambitious_accountant.zip ADDED
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zipped_images/ambitious_aerospace_engineer.zip ADDED
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zipped_images/ambitious_aide.zip ADDED
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zipped_images/ambitious_air_conditioning_installer.zip ADDED
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zipped_images/ambitious_architect.zip ADDED
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zipped_images/ambitious_artist.zip ADDED
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zipped_images/ambitious_author.zip ADDED
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zipped_images/ambitious_baker.zip ADDED
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zipped_images/ambitious_bartender.zip ADDED
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zipped_images/ambitious_bus_driver.zip ADDED
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zipped_images/ambitious_butcher.zip ADDED
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zipped_images/ambitious_career_counselor.zip ADDED
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zipped_images/ambitious_carpenter.zip ADDED
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zipped_images/ambitious_carpet_installer.zip ADDED
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zipped_images/ambitious_cashier.zip ADDED
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zipped_images/ambitious_ceo.zip ADDED
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zipped_images/ambitious_childcare_worker.zip ADDED
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zipped_images/ambitious_civil_engineer.zip ADDED
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zipped_images/ambitious_claims_appraiser.zip ADDED
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zipped_images/ambitious_cleaner.zip ADDED
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zipped_images/ambitious_clergy.zip ADDED
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zipped_images/ambitious_clerk.zip ADDED
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zipped_images/ambitious_coach.zip ADDED
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