| import os |
|
|
| from vbench2_beta_i2v.utils import init_submodules, save_json, load_json |
| from vbench import VBench |
| import importlib |
|
|
|
|
| class VBenchI2V(VBench): |
| def __init__(self, device, full_info_dir, output_path): |
| super().__init__(device, full_info_dir, output_path) |
| self.i2v_dims = ["i2v_subject", "i2v_background", "camera_motion"] |
| self.quality_dims = ["subject_consistency", "background_consistency", "aesthetic_quality", "imaging_quality", "temporal_flickering", "motion_smoothness", "dynamic_degree",] |
| |
| def build_full_dimension_list(self, ): |
| return self.i2v_dims + self.quality_dims |
|
|
| def evaluate(self, videos_path, name, dimension_list=None, custom_image_folder=None, mode='vbench_standard', local=False, read_frame=False, resolution="1-1", **kwargs): |
| results_dict = {} |
| if dimension_list is None: |
| dimension_list = self.build_full_dimension_list() |
| submodules_dict = init_submodules(dimension_list, local=local, read_frame=read_frame, resolution=resolution) |
| |
| cur_full_info_path = self.build_full_info_json(videos_path, name, dimension_list, custom_image_folder=custom_image_folder, mode=mode) |
| |
| for dimension in dimension_list: |
| try: |
| if dimension in self.i2v_dims: |
| dimension_module = importlib.import_module(f'vbench2_beta_i2v.{dimension}') |
| else: |
| dimension_module = importlib.import_module(f'vbench.{dimension}') |
| evaluate_func = getattr(dimension_module, f'compute_{dimension}') |
| except Exception as e: |
| raise NotImplementedError(f'UnImplemented dimension {dimension}!, {e}') |
| submodules_list = submodules_dict[dimension] |
| print(f'cur_full_info_path: {cur_full_info_path}') |
| results = evaluate_func(cur_full_info_path, self.device, submodules_list, **kwargs) |
| results_dict[dimension] = results |
| output_name = os.path.join(self.output_path, name+'_eval_results.json') |
| save_json(results_dict, output_name) |
| print(f'Evaluation results saved to {output_name}') |
|
|
