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from pathlib import Path
import os
import re
#Thanks ChatGPT
pattern = r'\bfrom_pretrained\(.*?pretrained_model_or_path\s*=\s*(.*?)(?:,|\))|filename\s*=\s*(.*?)(?:,|\))|(\w+_filename)\s*=\s*(.*?)(?:,|\))'
aux_dir = Path(__file__).parent / 'src' / 'custom_controlnet_aux'
VAR_DICT = dict(
HF_MODEL_NAME = "lllyasviel/Annotators",
DWPOSE_MODEL_NAME = "yzd-v/DWPose",
BDS_MODEL_NAME = "bdsqlsz/qinglong_controlnet-lllite",
DENSEPOSE_MODEL_NAME = "LayerNorm/DensePose-TorchScript-with-hint-image",
MESH_GRAPHORMER_MODEL_NAME = "hr16/ControlNet-HandRefiner-pruned",
SAM_MODEL_NAME = "dhkim2810/MobileSAM",
UNIMATCH_MODEL_NAME = "hr16/Unimatch",
DEPTH_ANYTHING_MODEL_NAME = "LiheYoung/Depth-Anything", #HF Space
DIFFUSION_EDGE_MODEL_NAME = "hr16/Diffusion-Edge"
)
re_result_dict = {}
for preprocc in os.listdir(aux_dir):
if preprocc in ["__pycache__", 'tests']: continue
if '.py' in preprocc: continue
f = open(aux_dir / preprocc / '__init__.py', 'r')
code = f.read()
matches = re.findall(pattern, code)
result = [match[0] or match[1] or match[3] for match in matches]
if not len(result):
print(preprocc)
continue
result = [el.replace("'", '').replace('"', '') for el in result]
result = [VAR_DICT.get(el, el) for el in result]
re_result_dict[preprocc] = result
f.close()
for preprocc, re_result in re_result_dict.items():
model_name, filenames = re_result[0], re_result[1:]
print(f"* {preprocc}: ", end=' ')
assests_md = ', '.join([f"[{model_name}/{filename}](https://huggingface.co/{model_name}/blob/main/{filename})" for filename in filenames])
print(assests_md)
preprocc = "dwpose"
model_name, filenames = VAR_DICT['DWPOSE_MODEL_NAME'], ["yolox_l.onnx", "dw-ll_ucoco_384.onnx"]
print(f"* {preprocc}: ", end=' ')
assests_md = ', '.join([f"[{model_name}/{filename}](https://huggingface.co/{model_name}/blob/main/{filename})" for filename in filenames])
print(assests_md)
preprocc = "yolo-nas"
model_name, filenames = "hr16/yolo-nas-fp16", ["yolo_nas_l_fp16.onnx", "yolo_nas_m_fp16.onnx", "yolo_nas_s_fp16.onnx"]
print(f"* {preprocc}: ", end=' ')
assests_md = ', '.join([f"[{model_name}/{filename}](https://huggingface.co/{model_name}/blob/main/{filename})" for filename in filenames])
print(assests_md)
preprocc = "dwpose-torchscript"
model_name, filenames = "hr16/DWPose-TorchScript-BatchSize5", ["dw-ll_ucoco_384_bs5.torchscript.pt", "rtmpose-m_ap10k_256_bs5.torchscript.pt"]
print(f"* {preprocc}: ", end=' ')
assests_md = ', '.join([f"[{model_name}/{filename}](https://huggingface.co/{model_name}/blob/main/{filename})" for filename in filenames])
print(assests_md) |