Spaces:
Running
Running
File size: 12,724 Bytes
f8946c1 17d0a32 08e184e 8dd4d48 08e184e 17d0a32 08e184e 17d0a32 08e184e 986653b 17d0a32 08e184e 8dd4d48 08e184e 8a5e8bc 08e184e f8946c1 08e184e 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 08e184e d0703ef 08e184e 17d0a32 08e184e d0703ef 08e184e 17d0a32 8dd4d48 17d0a32 c46a8d2 17d0a32 08e184e d52c0c4 08e184e 17d0a32 d0703ef 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 d0703ef 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 8dd4d48 17d0a32 8dd4d48 |
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 |
from toolbox import CatchException, update_ui, get_conf, select_api_key, get_log_folder
from crazy_functions.multi_stage.multi_stage_utils import GptAcademicState
def gen_image(llm_kwargs, prompt, resolution="1024x1024", model="dall-e-2", quality=None, style=None):
import requests, json, time, os
from request_llms.bridge_all import model_info
proxies = get_conf('proxies')
# Set up OpenAI API key and model
api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
chat_endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
# 'https://api.openai.com/v1/chat/completions'
img_endpoint = chat_endpoint.replace('chat/completions','images/generations')
# # Generate the image
url = img_endpoint
headers = {
'Authorization': f"Bearer {api_key}",
'Content-Type': 'application/json'
}
data = {
'prompt': prompt,
'n': 1,
'size': resolution,
'model': model,
'response_format': 'url'
}
if quality is not None:
data['quality'] = quality
if style is not None:
data['style'] = style
response = requests.post(url, headers=headers, json=data, proxies=proxies)
print(response.content)
try:
image_url = json.loads(response.content.decode('utf8'))['data'][0]['url']
except:
raise RuntimeError(response.content.decode())
# 文件保存到本地
r = requests.get(image_url, proxies=proxies)
file_path = f'{get_log_folder()}/image_gen/'
os.makedirs(file_path, exist_ok=True)
file_name = 'Image' + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.png'
with open(file_path+file_name, 'wb+') as f: f.write(r.content)
return image_url, file_path+file_name
def edit_image(llm_kwargs, prompt, image_path, resolution="1024x1024", model="dall-e-2"):
import requests, json, time, os
from request_llms.bridge_all import model_info
proxies = get_conf('proxies')
api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
chat_endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
# 'https://api.openai.com/v1/chat/completions'
img_endpoint = chat_endpoint.replace('chat/completions','images/edits')
# # Generate the image
url = img_endpoint
n = 1
headers = {
'Authorization': f"Bearer {api_key}",
}
make_transparent(image_path, image_path+'.tsp.png')
make_square_image(image_path+'.tsp.png', image_path+'.tspsq.png')
resize_image(image_path+'.tspsq.png', image_path+'.ready.png', max_size=1024)
image_path = image_path+'.ready.png'
with open(image_path, 'rb') as f:
file_content = f.read()
files = {
'image': (os.path.basename(image_path), file_content),
# 'mask': ('mask.png', open('mask.png', 'rb'))
'prompt': (None, prompt),
"n": (None, str(n)),
'size': (None, resolution),
}
response = requests.post(url, headers=headers, files=files, proxies=proxies)
print(response.content)
try:
image_url = json.loads(response.content.decode('utf8'))['data'][0]['url']
except:
raise RuntimeError(response.content.decode())
# 文件保存到本地
r = requests.get(image_url, proxies=proxies)
file_path = f'{get_log_folder()}/image_gen/'
os.makedirs(file_path, exist_ok=True)
file_name = 'Image' + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.png'
with open(file_path+file_name, 'wb+') as f: f.write(r.content)
return image_url, file_path+file_name
@CatchException
def 图片生成_DALLE2(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
"""
txt 输入栏用户输入的文本,例如需要翻译的一段话,再例如一个包含了待处理文件的路径
llm_kwargs gpt模型参数,如温度和top_p等,一般原样传递下去就行
plugin_kwargs 插件模型的参数,暂时没有用武之地
chatbot 聊天显示框的句柄,用于显示给用户
history 聊天历史,前情提要
system_prompt 给gpt的静默提醒
user_request 当前用户的请求信息(IP地址等)
"""
history = [] # 清空历史,以免输入溢出
if prompt.strip() == "":
chatbot.append((prompt, "[Local Message] 图像生成提示为空白,请在“输入区”输入图像生成提示。"))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新
return
chatbot.append(("您正在调用“图像生成”插件。", "[Local Message] 生成图像, 请先把模型切换至gpt-*。如果中文Prompt效果不理想, 请尝试英文Prompt。正在处理中 ....."))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 由于请求gpt需要一段时间,我们先及时地做一次界面更新
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
resolution = plugin_kwargs.get("advanced_arg", '1024x1024')
image_url, image_path = gen_image(llm_kwargs, prompt, resolution)
chatbot.append([prompt,
f'图像中转网址: <br/>`{image_url}`<br/>'+
f'中转网址预览: <br/><div align="center"><img src="{image_url}"></div>'
f'本地文件地址: <br/>`{image_path}`<br/>'+
f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新
@CatchException
def 图片生成_DALLE3(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
history = [] # 清空历史,以免输入溢出
if prompt.strip() == "":
chatbot.append((prompt, "[Local Message] 图像生成提示为空白,请在“输入区”输入图像生成提示。"))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新
return
chatbot.append(("您正在调用“图像生成”插件。", "[Local Message] 生成图像, 请先把模型切换至gpt-*。如果中文Prompt效果不理想, 请尝试英文Prompt。正在处理中 ....."))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 由于请求gpt需要一段时间,我们先及时地做一次界面更新
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
resolution_arg = plugin_kwargs.get("advanced_arg", '1024x1024-standard-vivid').lower()
parts = resolution_arg.split('-')
resolution = parts[0] # 解析分辨率
quality = 'standard' # 质量与风格默认值
style = 'vivid'
# 遍历检查是否有额外参数
for part in parts[1:]:
if part in ['hd', 'standard']:
quality = part
elif part in ['vivid', 'natural']:
style = part
image_url, image_path = gen_image(llm_kwargs, prompt, resolution, model="dall-e-3", quality=quality, style=style)
chatbot.append([prompt,
f'图像中转网址: <br/>`{image_url}`<br/>'+
f'中转网址预览: <br/><div align="center"><img src="{image_url}"></div>'
f'本地文件地址: <br/>`{image_path}`<br/>'+
f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新
class ImageEditState(GptAcademicState):
# 尚未完成
def get_image_file(self, x):
import os, glob
if len(x) == 0: return False, None
if not os.path.exists(x): return False, None
if x.endswith('.png'): return True, x
file_manifest = [f for f in glob.glob(f'{x}/**/*.png', recursive=True)]
confirm = (len(file_manifest) >= 1 and file_manifest[0].endswith('.png') and os.path.exists(file_manifest[0]))
file = None if not confirm else file_manifest[0]
return confirm, file
def lock_plugin(self, chatbot):
chatbot._cookies['lock_plugin'] = 'crazy_functions.图片生成->图片修改_DALLE2'
self.dump_state(chatbot)
def unlock_plugin(self, chatbot):
self.reset()
chatbot._cookies['lock_plugin'] = None
self.dump_state(chatbot)
def get_resolution(self, x):
return (x in ['256x256', '512x512', '1024x1024']), x
def get_prompt(self, x):
confirm = (len(x)>=5) and (not self.get_resolution(x)[0]) and (not self.get_image_file(x)[0])
return confirm, x
def reset(self):
self.req = [
{'value':None, 'description': '请先上传图像(必须是.png格式), 然后再次点击本插件', 'verify_fn': self.get_image_file},
{'value':None, 'description': '请输入分辨率,可选:256x256, 512x512 或 1024x1024, 然后再次点击本插件', 'verify_fn': self.get_resolution},
{'value':None, 'description': '请输入修改需求,建议您使用英文提示词, 然后再次点击本插件', 'verify_fn': self.get_prompt},
]
self.info = ""
def feed(self, prompt, chatbot):
for r in self.req:
if r['value'] is None:
confirm, res = r['verify_fn'](prompt)
if confirm:
r['value'] = res
self.dump_state(chatbot)
break
return self
def next_req(self):
for r in self.req:
if r['value'] is None:
return r['description']
return "已经收集到所有信息"
def already_obtained_all_materials(self):
return all([x['value'] is not None for x in self.req])
@CatchException
def 图片修改_DALLE2(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request):
# 尚未完成
history = [] # 清空历史
state = ImageEditState.get_state(chatbot, ImageEditState)
state = state.feed(prompt, chatbot)
state.lock_plugin(chatbot)
if not state.already_obtained_all_materials():
chatbot.append(["图片修改\n\n1. 上传图片(图片中需要修改的位置用橡皮擦擦除为纯白色,即RGB=255,255,255)\n2. 输入分辨率 \n3. 输入修改需求", state.next_req()])
yield from update_ui(chatbot=chatbot, history=history)
return
image_path = state.req[0]['value']
resolution = state.req[1]['value']
prompt = state.req[2]['value']
chatbot.append(["图片修改, 执行中", f"图片:`{image_path}`<br/>分辨率:`{resolution}`<br/>修改需求:`{prompt}`"])
yield from update_ui(chatbot=chatbot, history=history)
image_url, image_path = edit_image(llm_kwargs, prompt, image_path, resolution)
chatbot.append([prompt,
f'图像中转网址: <br/>`{image_url}`<br/>'+
f'中转网址预览: <br/><div align="center"><img src="{image_url}"></div>'
f'本地文件地址: <br/>`{image_path}`<br/>'+
f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新
state.unlock_plugin(chatbot)
def make_transparent(input_image_path, output_image_path):
from PIL import Image
image = Image.open(input_image_path)
image = image.convert("RGBA")
data = image.getdata()
new_data = []
for item in data:
if item[0] == 255 and item[1] == 255 and item[2] == 255:
new_data.append((255, 255, 255, 0))
else:
new_data.append(item)
image.putdata(new_data)
image.save(output_image_path, "PNG")
def resize_image(input_path, output_path, max_size=1024):
from PIL import Image
with Image.open(input_path) as img:
width, height = img.size
if width > max_size or height > max_size:
if width >= height:
new_width = max_size
new_height = int((max_size / width) * height)
else:
new_height = max_size
new_width = int((max_size / height) * width)
resized_img = img.resize(size=(new_width, new_height))
resized_img.save(output_path)
else:
img.save(output_path)
def make_square_image(input_path, output_path):
from PIL import Image
with Image.open(input_path) as img:
width, height = img.size
size = max(width, height)
new_img = Image.new("RGBA", (size, size), color="black")
new_img.paste(img, ((size - width) // 2, (size - height) // 2))
new_img.save(output_path)
|