Spaces:
Runtime error
Runtime error
File size: 3,138 Bytes
d2dd1cd 65516a6 f4c8778 0ff3cdf d2dd1cd cd875c3 7db21f1 f428d8f d06f4b9 3a8c535 f4c8778 f428d8f 3a8c535 d2dd1cd d1820b1 d2dd1cd d1820b1 83c7862 d2dd1cd d1820b1 d2dd1cd |
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 |
from FollowYourPose.test_followyourpose import *
import copy
import gradio as gr
from transformers import AutoTokenizer, CLIPTextModel
from huggingface_hub import snapshot_download
from inference_mmpose import *
import sys
sys.path.append('FollowYourPose')
def get_time_string() -> str:
x = datetime.datetime.now()
return f"{(x.year - 2000):02d}{x.month:02d}{x.day:02d}-{x.hour:02d}{x.minute:02d}{x.second:02d}"
class merge_config_then_run():
def __init__(self) -> None:
# Load the tokenizer
self.tokenizer = None
self.text_encoder = None
self.vae = None
self.unet = None
self.download_model()
self.mmpose = gr.Interface.load(name="spaces/fffiloni/mmpose-estimation")
def download_model(self):
REPO_ID = 'YueMafighting/FollowYourPose_v1'
snapshot_download(repo_id=REPO_ID, local_dir='./FollowYourPose/checkpoints/', local_dir_use_symlinks=False)
def run(
self,
data_path,
target_prompt,
num_steps,
guidance_scale,
video_type,
user_input_video=None,
start_sample_frame=0,
n_sample_frame=8,
stride=1,
left_crop=0,
right_crop=0,
top_crop=0,
bottom_crop=0,
):
if video_type == "Raw Video":
infer_skeleton(self.mmpose, data_path)
default_edit_config='./FollowYourPose/configs/pose_sample.yaml'
Omegadict_default_edit_config = OmegaConf.load(default_edit_config)
dataset_time_string = get_time_string()
config_now = copy.deepcopy(Omegadict_default_edit_config)
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,
"sampling_rate" : stride,
"offset": offset_dict,
}
config_now['validation_data'].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:
if isinstance(user_input_video, str):
config_now['validation_data']['path'] = user_input_video
elif hasattr(user_input_video, 'name') and user_input_video.name is not None:
config_now['validation_data']['path'] = user_input_video.name
config_now['validation_data']['prompts'] = [target_prompt]
# ddim config
config_now['validation_data']['guidance_scale'] = guidance_scale
config_now['validation_data']['num_inference_steps'] = num_steps
if video_type == "Raw Video":
config_now['skeleton_path'] = './mmpose_result.mp4'
else:
config_now['skeleton_path'] = data_path
save_path = test(**config_now)
mp4_path = save_path.replace('_0.gif', '_0_0_0.mp4')
return mp4_path
|