/
app.py
446 lines (381 loc) · 22 KB
/
app.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
# coding: utf-8
import os
import numpy as np
os.environ['CURL_CA_BUNDLE'] = ''
os.environ['MKL_SERVICE_FORCE_INTEL'] = '1'
try:
import detectron2
except:
os.system('pip install git+https://github.com/facebookresearch/detectron2.git')
from pathlib import Path
import sys
sys.path.insert(0, str(Path(__file__).resolve().parent / "third-party" / "lama"))
import random
from PIL import Image
import numpy as np
import argparse
from functools import partial
import gradio as gr
import gradio.themes.base as ThemeBase
from gradio.themes.utils import colors, fonts, sizes
from openai.error import APIConnectionError
# from iGPT.models import *
from iGPT.controllers import ConversationBot
import openai
from langchain.llms.openai import OpenAI
api_base = os.environ.get('OPENAI_API_BASE', None)
if api_base is not None:
openai.api_base = api_base
os.makedirs('image', exist_ok=True)
class ImageSketcher(gr.Image):
"""
Code is from https://github.com/ttengwang/Caption-Anything/blob/main/app.py#L32.
Fix the bug of gradio.Image that cannot upload with tool == 'sketch'.
"""
is_template = True # Magic to make this work with gradio.Block, don't remove unless you know what you're doing.
def __init__(self, **kwargs):
super().__init__(tool="sketch", **kwargs)
def preprocess(self, x):
if x is None:
return x
if self.tool == 'sketch' and self.source in ["upload", "webcam"]:
# assert isinstance(x, dict)
if isinstance(x, dict) and x['mask'] is None:
decode_image = gr.processing_utils.decode_base64_to_image(x['image'])
width, height = decode_image.size
mask = np.zeros((height, width, 4), dtype=np.uint8)
mask[..., -1] = 255
mask = self.postprocess(mask)
x['mask'] = mask
elif not isinstance(x, dict):
decode_image = gr.processing_utils.decode_base64_to_image(x)
width, height = decode_image.size
decode_image.save('sketch_test.png')
# print(width, height)
mask = np.zeros((height, width, 4), dtype=np.uint8)
mask[..., -1] = 255
mask = self.postprocess(mask)
x = {'image': x, 'mask': mask}
x = super().preprocess(x)
return x
class Seafoam(ThemeBase.Base):
def __init__(
self,
*,
primary_hue=colors.emerald,
secondary_hue=colors.blue,
neutral_hue=colors.gray,
spacing_size=sizes.spacing_md,
radius_size=sizes.radius_md,
text_size=sizes.text_lg,
font=(
fonts.GoogleFont("Quicksand"),
"ui-sans-serif",
"sans-serif",
),
font_mono=(
fonts.GoogleFont("IBM Plex Mono"),
"ui-monospace",
"monospace",
),
):
super().__init__(
primary_hue=primary_hue,
secondary_hue=secondary_hue,
neutral_hue=neutral_hue,
spacing_size=spacing_size,
radius_size=radius_size,
text_size=text_size,
font=font,
font_mono=font_mono,
)
super().set(
# body_background_fill="#D8E9EB",
body_background_fill_dark="#111111",
button_primary_background_fill="*primary_300",
button_primary_background_fill_hover="*primary_200",
button_primary_text_color="black",
button_secondary_background_fill="*secondary_300",
button_secondary_background_fill_hover="*secondary_200",
border_color_primary="#0BB9BF",
slider_color="*secondary_300",
slider_color_dark="*secondary_600",
block_title_text_weight="600",
block_border_width="3px",
block_shadow="*shadow_drop_lg",
button_shadow="*shadow_drop_lg",
button_large_padding="10px",
)
css='''
#image_upload {align-items: center; max-width: 640px}
'''
def cut_dialogue_history(history_memory, keep_last_n_words=500):
if history_memory is None or len(history_memory) == 0:
return history_memory
tokens = history_memory.split()
n_tokens = len(tokens)
print(f"history_memory:{history_memory}, n_tokens: {n_tokens}")
if n_tokens < keep_last_n_words:
return history_memory
paragraphs = history_memory.split('\n')
last_n_tokens = n_tokens
while last_n_tokens >= keep_last_n_words:
last_n_tokens -= len(paragraphs[0].split(' '))
paragraphs = paragraphs[1:]
return '\n' + '\n'.join(paragraphs)
def login_with_key(bot, debug, api_key):
# Just for debug
print('===>logging in')
user_state = [{}]
is_error = True
if debug:
user_state = bot.init_agent()
return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False, value=''), user_state
else:
if api_key and len(api_key) > 30:
print(api_key)
os.environ["OPENAI_API_KEY"] = api_key
openai.api_key = api_key
try:
llm = OpenAI(temperature=0)
llm('Hi!')
response = 'Success!'
is_error = False
user_state = bot.init_agent()
except Exception as err:
# gr.update(visible=True)
print(err)
response = 'Incorrect key, please input again'
is_error = True
else:
is_error = True
response = 'Incorrect key, please input again'
return gr.update(visible=not is_error), gr.update(visible=is_error), gr.update(visible=is_error, value=response), user_state
def change_input_type(flag):
if flag:
print('Using voice input.')
else:
print('Using text input.')
return gr.update(visible=not flag), gr.update(visible=flag)
def random_image():
root_path = './assets/images'
img_list = os.listdir(root_path)
img_item = random.sample(img_list, 1)[0]
return Image.open(os.path.join(root_path, img_item))
def random_video():
root_path = './assets/videos'
vid_list = os.listdir(root_path)
vid_item = random.sample(vid_list, 1)[0]
return os.path.join(root_path, vid_item)
def random_audio():
root_path = './assets/audio'
aud_list = os.listdir(root_path)
aud_item = random.sample(aud_list, 1)[0]
print(os.path.join(root_path, aud_item))
return os.path.join(root_path, aud_item)
def add_whiteboard():
# wb = np.ones((1080, 1920, 3), dtype=np.uint8) * 255
wb = np.ones((720, 1280, 3), dtype=np.uint8) * 255
return Image.fromarray(wb)
def change_max_iter(max_iters):
return gr.update(maximum=max_iters)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('-p', '--port', type=int, default=7862)
parser.add_argument('-d', '--debug', action='store_true')
parser.add_argument('--https', action='store_true')
parser.add_argument('--load', type=str, default="HuskyVQA_cuda:0,ImageOCRRecognition_cuda:0,SegmentAnything_cuda:0")
parser.add_argument('--tab', type=str, default="Audio,DragGAN,Image,Video")
parser.add_argument('-e', '--e-mode', action='store_true')
args = parser.parse_args()
load_dict = {e.split('_')[0].strip(): e.split('_')[1].strip() for e in args.load.split(',')}
bot = ConversationBot(load_dict=load_dict, e_mode=args.e_mode)
with gr.Blocks(theme=Seafoam(), css=css) as demo:
state = gr.State([])
# user_state is dict. Keys: [agent, memory, image_path, video_path, seg_mask, image_caption, OCR_res, ...]
user_state = gr.State([])
gr.HTML(
"""
<div align='center'> <img src='/file=./assets/gvlab_logo.png' style='height:70px'/> </div>
<p align="center"><a href="https://github.com/OpenGVLab/InternGPT"><b>GitHub</b></a>
<a href="https://arxiv.org/pdf/2305.05662.pdf"><b>Report</b></a>
<a href="https://github.com/OpenGVLab/InternGPT/assets/13723743/8fd9112f-57d9-4871-a369-4e1929aa2593"><b>Video Demo</b></a>
<a href="https://github.com/OpenGVLab/InternGPT/tree/main#imagebind_demo"><b>Video Demo with ImageBind</b></a>
<a href="https://github.com/OpenGVLab/InternGPT/tree/main#draggan_demo"><b>Video Demo with DragGAN</b></a></p>
"""
)
with gr.Row(visible=True, elem_id='login') as login:
with gr.Column(scale=0.6, min_width=0) :
openai_api_key_text = gr.Textbox(
placeholder="Input openAI API key",
show_label=False,
label="OpenAI API Key",
lines=1,
type="password").style(container=False)
with gr.Column(scale=0.4, min_width=0):
key_submit_button = gr.Button(value="Please log in with your OpenAI API Key", interactive=True, variant='primary').style(container=False)
with gr.Row(visible=False) as user_interface:
with gr.Column(scale=0.5, elem_id="text_input") as chat_part:
chatbot = gr.Chatbot(elem_id="chatbot", label="InternGPT").style(height=360)
with gr.Row(visible=True) as input_row:
with gr.Column(min_width=0) as text_col:
txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter, or upload an image").style(
container=False)
audio2text_input = gr.Audio(source="microphone", type="filepath", visible=False)
with gr.Row(visible=True) as input_btn:
with gr.Column(scale=0.5, min_width=0):
audio_switch = gr.Checkbox(label="🎤 Voice Assistant", elem_id='audio_switch', info=None)
with gr.Column(scale=0.5, min_width=20):
send_btn = gr.Button("📤 Send", variant="primary", visible=True)
with gr.Column(elem_id="visual_input", scale=0.5) as img_part:
if 'Audio' in args.tab:
with gr.Tab("Audio (with ImageBind)", elem_id='audio_tab') as audio_tab:
audio_input = gr.Audio(source="upload", type="filepath", visible=True, elem_id="audio_upload").style(height=360)
add_aud_example = gr.Button("📻 Audio Example", variant="primary")
add_aud_example.click(random_audio, [], [audio_input,]).then(
bot.upload_audio, [audio_input, state, user_state],
[chatbot, state, user_state])
audio_input.upload(
bot.upload_audio, [audio_input, state, user_state],
[chatbot, state, user_state])
if 'DragGAN' in args.tab:
with gr.Tab("DragGAN", elem_id='drag_gan_tab') as drag_gan_tab:
drag_image = gr.Image(interactive=False).style(height=340)
with gr.Row(elem_id='drag_gan_btn') as drag_btn_row:
with gr.Column(scale=0.33, min_width=0):
drag_new_img_btn = gr.Button('🖼️ New Image', variant='primary')
with gr.Column(scale=0.33, min_width=0):
drag_btn = gr.Button('🖱︎ Drag It', variant='primary')
with gr.Column(scale=0.33, min_width=0):
drag_reset_btn = gr.Button('🧹 Clear Points', variant='primary')
with gr.Row(elem_id='drag_gan_progress'):
with gr.Column(scale=0.5, min_width=0):
drag_max_iters = gr.Slider(1, 100, 25, step=1, label='Max Iterations', elem_id='drag_max_iters')
with gr.Column(scale=0.5, min_width=0):
progress = gr.Slider(value=0, maximum=25, label='Progress', interactive=False, elem_id='progress')
drag_new_img_btn.click(bot.gen_new_image, [state, user_state], [drag_image, chatbot, state, user_state])
drag_image.select(bot.save_points_for_drag_gan, [drag_image, user_state, ], [drag_image, user_state, ])
drag_btn.click(
bot.drag_it, [drag_image, drag_max_iters, state, user_state], [drag_image, progress, chatbot, state, user_state]
)
drag_max_iters.change(change_max_iter, [drag_max_iters,], [progress, ])
drag_reset_btn.click(bot.reset_drag_points, [drag_image, user_state], [drag_image, user_state, ])
drag_gan_tab.select(
bot.gen_new_image, [state, user_state], [drag_image, chatbot, state, user_state])
if 'Image' in args.tab:
with gr.Tab("Image", elem_id='image_tab') as img_tab:
click_img = ImageSketcher(type="pil", interactive=True, brush_radius=15, elem_id="image_upload").style(height=360)
with gr.Row() as img_btn:
with gr.Column(scale=0.25, min_width=0):
process_seg_btn = gr.Button(value="👆 Pick", variant="primary", elem_id="process_seg_btn")
with gr.Column(scale=0.25, min_width=0):
process_ocr_btn = gr.Button(value="🔍 OCR", variant="primary", elem_id="process_ocr_btn")
with gr.Column(scale=0.25, min_width=0):
process_save_btn = gr.Button(value="📁 Save", variant="primary", elem_id="process_save_btn")
with gr.Column(scale=0.25, min_width=0):
clear_btn = gr.Button(value="🗑️ Clear All", elem_id="clear_btn")
with gr.Row(visible=True) as img_example:
with gr.Column(scale=0.5, min_width=0, visible=True) :
add_img_example = gr.Button("🖼️ Image Example", variant="primary")
with gr.Column(scale=0.5, min_width=0):
whiteboard_mode = gr.Button("⬜️ Whiteboard Mode", variant="primary", visible=True)
add_img_example.click(random_image, [], [click_img,]).then(
bot.upload_image, [click_img, state, user_state],
[chatbot, state, user_state])
whiteboard_mode.click(add_whiteboard, [], [click_img, ])
click_img.upload(lambda: gr.update(interactive=False), [], [send_btn]).then(
bot.upload_image, [click_img, state, user_state],
[chatbot, state, user_state]).then(
lambda: gr.update(interactive=True), [], [send_btn])
process_ocr_btn.click(
lambda: gr.update(interactive=False), [], [process_ocr_btn]).then(
bot.process_ocr, [click_img, state, user_state], [click_img, chatbot, state, user_state]).then(
lambda: gr.update(interactive=True), [], [process_ocr_btn]
)
process_seg_btn.click(
lambda: gr.update(interactive=False), [], [process_seg_btn]).then(
bot.process_seg, [click_img, state, user_state], [click_img, chatbot, state, user_state]).then(
lambda: gr.update(interactive=True), [], [process_seg_btn]
)
process_save_btn.click(
lambda: gr.update(interactive=False), [], [process_save_btn]).then(
bot.process_save, [click_img, state, user_state], [click_img, chatbot, state, user_state]).then(
lambda: gr.update(interactive=True), [], [process_save_btn]
)
clear_func = partial(bot.clear_user_state, True)
clear_btn.click(lambda: None, [], [click_img, ]).then(
lambda: [], None, state).then(
clear_func, [user_state, ], [user_state, ]).then(
lambda: None, None, chatbot
).then(lambda: '', None, [txt, ])
if 'Video' in args.tab:
with gr.Tab("Video", elem_id='video_tab') as video_tab:
video_input = gr.Video(interactive=True, include_audio=True, elem_id="video_upload").style(height=360)
add_vid_example = gr.Button("📽 Video Example", variant="primary")
add_vid_example.click(random_video, [], [video_input,]).then(
bot.upload_video, [video_input, state, user_state],
[chatbot, state, user_state])
video_input.upload(
bot.upload_video, [video_input, state, user_state],
[chatbot, state, user_state])
clear_func = partial(bot.clear_user_state, False)
video_input.clear(clear_func, [user_state, ], [user_state, ])
login_func = partial(login_with_key, bot, args.debug)
openai_api_key_text.submit(login_func, [openai_api_key_text], [user_interface, openai_api_key_text, key_submit_button, user_state])
key_submit_button.click(login_func, [openai_api_key_text, ], [user_interface, openai_api_key_text, key_submit_button, user_state])
txt.submit(
lambda: gr.update(interactive=False), [], [send_btn]).then(
lambda: gr.update(interactive=False), [], [txt]).then(
lambda: gr.update(interactive=False), [], [audio_switch]).then(
bot.run_text, [txt, state, user_state], [chatbot, state, user_state]).then(
lambda: "", None, [txt, ]).then(
lambda: gr.update(interactive=True), [], [txt]).then(
lambda: gr.update(interactive=True), [], [send_btn]
).then(
lambda: gr.update(interactive=True), [], [audio_switch]
)
send_btn.click(
lambda: gr.update(interactive=False), [], [send_btn]).then(
lambda: gr.update(interactive=False), [], [txt]).then(
lambda: gr.update(interactive=False), [], [audio_switch]).then(
bot.run_task, [audio_switch, txt, audio2text_input, state, user_state], [chatbot, state, user_state]).then(
lambda: "", None, [txt, ]).then(
lambda: gr.update(interactive=True), [], [send_btn]).then(
lambda: gr.update(interactive=True), [], [txt]
).then(
lambda: gr.update(interactive=True), [], [audio_switch]
)
audio_switch.change(change_input_type, [audio_switch, ], [txt, audio2text_input])
gr.Markdown(
'''
**User Manual:**
Update:
(2023.05.24) We now support [DragGAN](https://github.com/Zeqiang-Lai/DragGAN). You can try it as follows:
- Click the button `New Image`;
- Click the image where blue denotes the start point and red denotes the end point;
- Notice that the number of blue points is the same as the number of red points. Then you can click the button `Drag It`;
- After processing, you will receive an edited image and a video that visualizes the editing process.
<br>(2023.05.18) We now support [ImageBind](https://github.com/facebookresearch/ImageBind). If you want to generate a new image conditioned on audio, you can upload an audio file in advance:
- To **generate a new image from a single audio file**, you can send the message like: `"generate a real image from this audio"`;
- To **generate a new image from audio and text**, you can send the message like: `"generate a real image from this audio and {your prompt}"`;
- To **generate a new image from audio and image**, you need to upload an image and then send the message like: `"generate a new image from above image and audio"`;
<br>After uploading the image, you can have a **multi-modal dialogue** by sending messages like: `"what is it in the image?"` or `"what is the background color of the image?"`.
You also can interactively operate, edit or generate the image as follows:
- You can click the image and press the button **`Pick`** to **visualize the segmented region** or press the button **`OCR`** to **recognize the words** at chosen position;
- To **remove the masked region** in the image, you can send the message like: `"remove the masked region"`;
- To **replace the masked region** in the image, you can send the message like: `"replace the masked region with {your prompt}"`;
- To **generate a new image**, you can send the message like: `"generate a new image based on its segmentation describing {your prompt}"`.
- To **create a new image by your scribble**, you should press button **`Whiteboard`** and draw in the board. After drawing, you need to press the button **`Save`** and send the message like: `"generate a new image based on this scribble describing {your prompt}"`.
'''
)
gr.HTML(
"""
<body>
<p style="font-family:verdana;color:#11AA00";>More features are coming soon. Hope you have fun with our demo!</p>
</body>
"""
)
if args.https:
demo.queue().launch(server_name="0.0.0.0", ssl_certfile="./certificate/cert.pem", ssl_keyfile="./certificate/key.pem", ssl_verify=False, server_port=args.port)
else:
demo.queue().launch(server_name="0.0.0.0", server_port=args.port)