Spaces:
Runtime error
Runtime error
File size: 3,015 Bytes
b57c333 afd7574 b57c333 afd7574 b57c333 a06cc14 5e82734 b57c333 afd7574 b57c333 |
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 |
from FateZero.test_fatezero import *
import copy
import gradio as gr
def merge_config_then_run(
model_id,
data_path,
source_prompt,
target_prompt,
cross_replace_steps,
self_replace_steps,
enhance_words,
enhance_words_value,
num_steps,
guidance_scale,
user_input_video,
# Temporal and spatial crop of the video
start_sample_frame,
n_sample_frame,
stride,
left_crop,
right_crop,
top_crop,
bottom_crop,
):
# , ] = inputs
default_edit_config='FateZero/config/low_resource_teaser/jeep_watercolor_ddim_10_steps.yaml'
Omegadict_default_edit_config = OmegaConf.load(default_edit_config)
dataset_time_string = get_time_string()
config_now = copy.deepcopy(Omegadict_default_edit_config)
print(f"config_now['pretrained_model_path'] = model_id {model_id}")
# config_now['pretrained_model_path'] = model_id
config_now['train_dataset']['prompt'] = source_prompt
config_now['train_dataset']['path'] = data_path
# ImageSequenceDataset_dict = { }
offset_dict = {
"left": left_crop,
"right": right_crop,
"top": top_crop,
"bottom": bottom_crop,
}
ImageSequenceDataset_dict = {
"start_sample_frame" : start_sample_frame,
"n_sample_frame" : n_sample_frame,
"stride" : stride,
"offset": offset_dict,
}
config_now['train_dataset'].update(ImageSequenceDataset_dict)
if user_input_video and data_path is None:
raise gr.Error('You need to upload a video or choose a provided video')
if user_input_video is not None and user_input_video.name is not None:
config_now['train_dataset']['path'] = user_input_video.name
config_now['validation_sample_logger_config']['prompts'] = [target_prompt]
# fatezero config
p2p_config_now = copy.deepcopy(config_now['validation_sample_logger_config']['p2p_config'][0])
p2p_config_now['cross_replace_steps']['default_'] = cross_replace_steps
p2p_config_now['self_replace_steps'] = self_replace_steps
p2p_config_now['eq_params']['words'] = enhance_words.split(" ")
p2p_config_now['eq_params']['values'] = [enhance_words_value,]*len(p2p_config_now['eq_params']['words'])
config_now['validation_sample_logger_config']['p2p_config'][0] = copy.deepcopy(p2p_config_now)
# ddim config
config_now['validation_sample_logger_config']['guidance_scale'] = guidance_scale
config_now['validation_sample_logger_config']['num_inference_steps'] = num_steps
logdir = default_edit_config.replace('config', 'result').replace('.yml', '').replace('.yaml', '')+f'_{dataset_time_string}'
config_now['logdir'] = logdir
print(f'Saving at {logdir}')
save_path = test(config=default_edit_config, **config_now)
mp4_path = save_path.replace('_0.gif', '_0_0_0.mp4')
return mp4_path
if __name__ == "__main__":
run()
|