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on
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Running
on
Zero
from .imagen_museum import TASK_DICT, DOMAIN | |
from .imagen_museum import fetch_indexes, fetch_indexes_no_csv | |
import random | |
ARENA_TO_IG_MUSEUM = {"LCM(v1.5/XL)":"LCM", | |
"PlayGroundV2.5": "PlayGroundV2_5"} | |
def draw2_from_imagen_museum(task, model_name1, model_name2): | |
task_name = TASK_DICT[task] | |
model_name1 = ARENA_TO_IG_MUSEUM[model_name1] if model_name1 in ARENA_TO_IG_MUSEUM else model_name1 | |
model_name2 = ARENA_TO_IG_MUSEUM[model_name2] if model_name2 in ARENA_TO_IG_MUSEUM else model_name2 | |
domain = DOMAIN | |
baselink = domain + task_name | |
matched_results = fetch_indexes(baselink) | |
r = random.Random() | |
uid, value = r.choice(list(matched_results.items())) | |
image_link_1 = baselink + "/" + model_name1 + "/" + uid | |
image_link_2 = baselink + "/" + model_name2 + "/" + uid | |
if task == "t2i": # Image Gen | |
prompt = value['prompt'] | |
return [[image_link_1, image_link_2], [prompt]] | |
if task == "tie": # Image Edit | |
instruction = value['instruction'] | |
input_caption = value['source_global_caption'] | |
output_caption = value['target_global_caption'] | |
source_image_link = baselink + "/" + "input" + "/" + uid | |
return [[source_image_link, image_link_1, image_link_2], [input_caption, output_caption, instruction]] | |
else: | |
raise ValueError("Task not supported") | |
def draw_from_imagen_museum(task, model_name): | |
task_name = TASK_DICT[task] | |
model_name = ARENA_TO_IG_MUSEUM[model_name] if model_name in ARENA_TO_IG_MUSEUM else model_name | |
domain = DOMAIN | |
baselink = domain + task_name | |
matched_results = fetch_indexes(baselink) | |
r = random.Random() | |
uid, value = r.choice(list(matched_results.items())) | |
model = model_name | |
image_link = baselink + "/" + model + "/" + uid | |
print(image_link) | |
if task == "t2i": # Image Gen | |
prompt = value['prompt'] | |
return [image_link, prompt] | |
if task == "tie": # Image Edit | |
instruction = value['instruction'] | |
input_caption = value['source_global_caption'] | |
output_caption = value['target_global_caption'] | |
source_image_link = baselink + "/" + "input" + "/" + uid | |
return [[source_image_link, image_link], [input_caption, output_caption, instruction]] | |
else: | |
raise ValueError("Task not supported") | |
def draw2_from_videogen_museum(task, model_name1, model_name2): | |
domain = "https://github.com/ChromAIca/VideoGenMuseum/raw/main/Museum/" | |
baselink = domain + "VideoGenHub_Text-Guided_VG" | |
matched_results = fetch_indexes_no_csv(baselink) | |
r = random.Random() | |
uid, value = r.choice(list(matched_results.items())) | |
video_link_1 = baselink + "/" + model_name1 + "/" + uid | |
video_link_2 = baselink + "/" + model_name2 + "/" + uid | |
if task == "t2v": # Video Gen | |
prompt = value['prompt_en'] | |
return [[video_link_1, video_link_2], [prompt]] | |
else: | |
raise ValueError("Task not supported") | |
def draw_from_videogen_museum(task, model_name): | |
domain = "https://github.com/ChromAIca/VideoGenMuseum/raw/main/Museum/" | |
baselink = domain + "VideoGenHub_Text-Guided_VG" | |
matched_results = fetch_indexes_no_csv(baselink) | |
r = random.Random() | |
uid, value = r.choice(list(matched_results.items())) | |
model = model_name | |
video_link = baselink + "/" + model + "/" + uid | |
print(video_link) | |
if task == "t2v": # Video Gen | |
prompt = value['prompt_en'] | |
return [video_link, prompt] | |
else: | |
raise ValueError("Task not supported") |