File size: 8,136 Bytes
fb515d0 |
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 |
import discord
from gradio_client import Client
import os
import random
from PIL import Image
import asyncio
import glob
import pathlib
HF_TOKEN = os.getenv("HF_TOKEN")
deepfloydif_client = Client("huggingface-projects/IF", HF_TOKEN)
BOT_USER_ID = 1086256910572986469 if os.getenv("TEST_ENV", False) else 1102236653545861151
DEEPFLOYDIF_CHANNEL_ID = 1121834257959092234 if os.getenv("TEST_ENV", False) else 1119313215675973714
def deepfloydif_stage_1_inference(prompt):
"""Generates an image based on a prompt"""
negative_prompt = ""
seed = random.randint(0, 1000)
number_of_images = 4
guidance_scale = 7
custom_timesteps_1 = "smart50"
number_of_inference_steps = 50
(
stage_1_images,
stage_1_param_path,
path_for_stage_2_upscaling,
) = deepfloydif_client.predict(
prompt,
negative_prompt,
seed,
number_of_images,
guidance_scale,
custom_timesteps_1,
number_of_inference_steps,
api_name="/generate64",
)
return [stage_1_images, stage_1_param_path, path_for_stage_2_upscaling]
def deepfloydif_stage_2_inference(index, path_for_stage_2_upscaling):
"""Upscales one of the images from deepfloydif_stage_1_inference based on the chosen index"""
selected_index_for_stage_2 = index
seed_2 = 0
guidance_scale_2 = 4
custom_timesteps_2 = "smart50"
number_of_inference_steps_2 = 50
result_path = deepfloydif_client.predict(
path_for_stage_2_upscaling,
selected_index_for_stage_2,
seed_2,
guidance_scale_2,
custom_timesteps_2,
number_of_inference_steps_2,
api_name="/upscale256",
)
return result_path
async def react_1234(reaction_emojis, combined_image_dfif):
"""Sets up 4 reaction emojis so the user can choose an image to upscale for deepfloydif"""
for emoji in reaction_emojis:
await combined_image_dfif.add_reaction(emoji)
def load_image(png_files, stage_1_images):
"""Opens images as variables so we can combine them later"""
results = []
for file in png_files:
png_path = os.path.join(stage_1_images, file)
results.append(Image.open(png_path))
return results
def combine_images(png_files, stage_1_images, partial_path):
if os.environ.get("TEST_ENV") == "True":
print("Combining images for deepfloydif_stage_1")
images = load_image(png_files, stage_1_images)
combined_image = Image.new("RGB", (images[0].width * 2, images[0].height * 2))
combined_image.paste(images[0], (0, 0))
combined_image.paste(images[1], (images[0].width, 0))
combined_image.paste(images[2], (0, images[0].height))
combined_image.paste(images[3], (images[0].width, images[0].height))
combined_image_path = os.path.join(stage_1_images, f"{partial_path}.png")
combined_image.save(combined_image_path)
return combined_image_path
async def deepfloydif_stage_1(interaction, prompt, client):
"""DeepfloydIF command (generate images with realistic text using slash commands)"""
try:
if interaction.user.id != BOT_USER_ID:
if interaction.channel.id == DEEPFLOYDIF_CHANNEL_ID:
if os.environ.get("TEST_ENV") == "True":
print("Safety checks passed for deepfloydif_stage_1")
await interaction.response.send_message("Working on it!")
channel = interaction.channel
# interaction.response message can't be used to create a thread, so we create another message
message = await channel.send("DeepfloydIF Thread")
thread = await message.create_thread(name=f"{prompt}", auto_archive_duration=60)
await thread.send(
"[DISCLAIMER: HuggingBot is a **highly experimental** beta feature; Additional information on the"
" DeepfloydIF model can be found here: https://huggingface.co/spaces/DeepFloyd/IF"
)
await thread.send(f"{interaction.user.mention} Generating images in thread, can take ~1 minute...")
loop = asyncio.get_running_loop()
result = await loop.run_in_executor(None, deepfloydif_stage_1_inference, prompt)
stage_1_images = result[0]
path_for_stage_2_upscaling = result[2]
partial_path = pathlib.Path(path_for_stage_2_upscaling).name
png_files = list(glob.glob(f"{stage_1_images}/**/*.png"))
if png_files:
combined_image_path = combine_images(png_files, stage_1_images, partial_path)
if os.environ.get("TEST_ENV") == "True":
print("Images combined for deepfloydif_stage_1")
with open(combined_image_path, "rb") as f:
combined_image_dfif = await thread.send(
f"{interaction.user.mention} React with the image number you want to upscale!",
file=discord.File(f, f"{partial_path}.png"),
)
emoji_list = ["↖️", "↗️", "↙️", "↘️"]
await react_1234(emoji_list, combined_image_dfif)
else:
await thread.send(f"{interaction.user.mention} No PNG files were found, cannot post them!")
except Exception as e:
print(f"Error: {e}")
async def deepfloydif_stage_2_react_check(reaction, user):
"""Checks for a reaction in order to call dfif2"""
try:
if os.environ.get("TEST_ENV") == "True":
print("Running deepfloydif_stage_2_react_check")
global BOT_USER_ID
global DEEPFLOYDIF_CHANNEL_ID
if user.id != BOT_USER_ID:
thread = reaction.message.channel
thread_parent_id = thread.parent.id
if thread_parent_id == DEEPFLOYDIF_CHANNEL_ID:
if reaction.message.attachments:
if user.id == reaction.message.mentions[0].id:
attachment = reaction.message.attachments[0]
image_name = attachment.filename
partial_path = image_name[:-4]
full_path = "/tmp/" + partial_path
emoji = reaction.emoji
if emoji == "↖️":
index = 0
elif emoji == "↗️":
index = 1
elif emoji == "↙️":
index = 2
elif emoji == "↘️":
index = 3
path_for_stage_2_upscaling = full_path
thread = reaction.message.channel
await deepfloydif_stage_2(
index,
path_for_stage_2_upscaling,
thread,
)
except Exception as e:
print(f"Error: {e} (known error, does not cause issues, low priority)")
async def deepfloydif_stage_2(index: int, path_for_stage_2_upscaling, thread):
"""upscaling function for images generated using /deepfloydif"""
try:
if os.environ.get("TEST_ENV") == "True":
print("Running deepfloydif_stage_2")
if index == 0:
position = "top left"
elif index == 1:
position = "top right"
elif index == 2:
position = "bottom left"
elif index == 3:
position = "bottom right"
await thread.send(f"Upscaling the {position} image...")
# run blocking function in executor
loop = asyncio.get_running_loop()
result_path = await loop.run_in_executor(
None, deepfloydif_stage_2_inference, index, path_for_stage_2_upscaling
)
with open(result_path, "rb") as f:
await thread.send("Here is the upscaled image!", file=discord.File(f, "result.png"))
await thread.edit(archived=True)
except Exception as e:
print(f"Error: {e}") |