You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
import os.path
|
|
from concurrent.futures import ProcessPoolExecutor
|
|
|
|
import numpy as np
|
|
import deepdanbooru as dd
|
|
import tensorflow as tf
|
|
|
|
|
|
def _load_tf_and_return_tags(pil_image, threshold):
|
|
this_folder = os.path.dirname(__file__)
|
|
model_path = os.path.join(this_folder, '..', 'models', 'deepbooru', 'deepdanbooru-v3-20211112-sgd-e28')
|
|
|
|
model_good = False
|
|
for path_candidate in [model_path, os.path.dirname(model_path)]:
|
|
if os.path.exists(os.path.join(path_candidate, 'project.json')):
|
|
model_path = path_candidate
|
|
model_good = True
|
|
if not model_good:
|
|
return ("Download https://github.com/KichangKim/DeepDanbooru/releases/download/v3-20211112-sgd-e28/"
|
|
"deepdanbooru-v3-20211112-sgd-e28.zip unpack and put into models/deepbooru")
|
|
|
|
tags = dd.project.load_tags_from_project(model_path)
|
|
model = dd.project.load_model_from_project(
|
|
model_path, compile_model=True
|
|
)
|
|
|
|
width = model.input_shape[2]
|
|
height = model.input_shape[1]
|
|
image = np.array(pil_image)
|
|
image = tf.image.resize(
|
|
image,
|
|
size=(height, width),
|
|
method=tf.image.ResizeMethod.AREA,
|
|
preserve_aspect_ratio=True,
|
|
)
|
|
image = image.numpy() # EagerTensor to np.array
|
|
image = dd.image.transform_and_pad_image(image, width, height)
|
|
image = image / 255.0
|
|
image_shape = image.shape
|
|
image = image.reshape((1, image_shape[0], image_shape[1], image_shape[2]))
|
|
|
|
y = model.predict(image)[0]
|
|
|
|
result_dict = {}
|
|
|
|
for i, tag in enumerate(tags):
|
|
result_dict[tag] = y[i]
|
|
result_tags_out = []
|
|
result_tags_print = []
|
|
for tag in tags:
|
|
if result_dict[tag] >= threshold:
|
|
if tag.startswith("rating:"):
|
|
continue
|
|
result_tags_out.append(tag)
|
|
result_tags_print.append(f'{result_dict[tag]} {tag}')
|
|
|
|
print('\n'.join(sorted(result_tags_print, reverse=True)))
|
|
|
|
return ', '.join(result_tags_out)
|
|
|
|
|
|
def get_deepbooru_tags(pil_image, threshold=0.5):
|
|
with ProcessPoolExecutor() as executor:
|
|
f = executor.submit(_load_tf_and_return_tags, pil_image, threshold)
|
|
ret = f.result() # will rethrow any exceptions
|
|
return ret |