init_code

lmm_utils/sim_utils.py

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+import shutil
+from pathlib import Path
+
+import yaml
+
+import pygarment.data_config as data_config
+from assets.bodies.body_params import BodyParameters
+from assets.garment_programs.meta_garment import MetaGarment
+from pygarment.data_config import Properties
+from pygarment.meshgen.boxmeshgen import BoxMesh
+from pygarment.meshgen.sim_config import PathCofig
+# from pygarment.meshgen.simulation import run_sim
+
+
+#Convert the yaml file directly into an output plate
+def garmentyaml_folder2json_folder(input_folder='', output_folder='',
+                                   body_to_use='neutral'):
+    ''' Convert the yaml files of the input folder to json files and save them in the output folder There is a folder with a yaml file name under the output folder, which contains JSON files and boilerplate images
+    Args:
+        input_folder(string): Enter a folder
+        output_folder (string): The output folder
+        body_to_use (string): Select a human body parameter
+    '''
+
+    bodies_measurements = {
+        # Our model
+        'neutral': './assets/bodies/mean_all.yaml',
+        'mean_female': './assets/bodies/mean_female.yaml',
+        'mean_male': './assets/bodies/mean_male.yaml',
+
+        # SMPL
+        'f_smpl': './assets/bodies/f_smpl_average_A40.yaml',
+        'm_smpl': './assets/bodies/m_smpl_average_A40.yaml',
+        #t pose
+        'mean_all_tpose': './assets/bodies/mean_all_tpose.yaml'
+    }
+    body_to_use = body_to_use # CHANGE HERE to use different set of body measurements
+    # body_to_use = 'mean_all_tpose'
+    body = BodyParameters(bodies_measurements[body_to_use])
+
+    design_files = {
+        't-shirt': './assets/design_params/t-shirt.yaml',
+        # Add paths HERE to load other parameters
+    }
+
+    pattern_dir = input_folder  # This is the input file, write the yaml folder here
+    design_files_list = [file for file in Path(pattern_dir).iterdir() if file.suffix == '.yaml']
+
+    design_files_stem = [item.stem for item in design_files_list]
+    design_files_list = [str(item) for item in design_files_list]
+    print(design_files_list)
+    design_files = {
+        k: v for k, v in zip(design_files_stem, design_files_list)
+
+    }
+
+    designs = {}
+    for df in design_files:
+        with open(design_files[df], 'r') as f:
+            designs[df] = yaml.safe_load(f)['design']
+
+    test_garments = []
+    for df in designs:
+        try:
+            garment = MetaGarment(df, body, designs[df])
+            test_garments.append(garment)
+        except Exception as e:
+            print(f"An error occurred with {df}: {e}")
+            continue
+    outpath = Path(output_folder)  # This is the folder for the output
+    outpath.mkdir(parents=True, exist_ok=True)
+
+    for piece in test_garments:
+        pattern = piece.assembly()
+
+        if piece.is_self_intersecting():
+            print(f'{piece.name} is Self-intersecting')
+
+        folder = pattern.serialize(
+            outpath,
+            tag='',
+            to_subfolder=True,
+            with_3d=False, with_text=False, view_ids=False,
+            with_printable=True
+        )
+
+        body.save(folder)
+        if piece.name in design_files:
+            shutil.copy(design_files[piece.name], folder)
+        else:
+            shutil.copy(design_files['base'], folder)
+
+        print(f'Success! {piece.name} saved to {folder}')
+
+
+def json2modelfolder(input_json):
+    ''' If you simulate a json file, you will save a folder in the directory where the json file is located, removing the specifiction ending as the folder name, and containing all the simulated information
+    Args：
+        input_json (string): A json file that needs to be mocked
+
+    '''
+    props = data_config.Properties('./assets/Sim_props/default_sim_props.yaml')
+    props.set_section_stats('sim', fails={}, sim_time={}, spf={}, fin_frame={}, body_collisions={}, self_collisions={})
+    props.set_section_stats('render', render_time={})
+
+    input_path = Path(input_json)
+    garment_name, _, _ = input_path.stem.rpartition('_')  # assuming ending in '_specification'
+    # garment_name = os.path.splitext(os.path.basename(input_path))[0]
+    sys_props = data_config.Properties('./system.json')
+    paths = PathCofig(
+        in_element_path=input_path.parent,
+        out_path=input_path.parent,
+        in_name=garment_name,
+        body_name='mean_all',  # 'f_smpl_average_A40'
+        smpl_body=False,  # NOTE: depends on chosen body model
+        add_timestamp=False
+    )
+
+    # Generate and save garment box mesh (if not existent)
+    print(f"Generate box mesh of {garment_name} with resolution {props['sim']['config']['resolution_scale']}...")
+    print('\nGarment load: ', paths.in_g_spec)
+
+    garment_box_mesh = BoxMesh(paths.in_g_spec, props['sim']['config']['resolution_scale'])
+    garment_box_mesh.load()
+    garment_box_mesh.serialize(
+        paths, store_panels=False, uv_config=props['render']['config']['uv_texture'])
+
+    props.serialize(paths.element_sim_props)
+
+    run_sim(
+        garment_box_mesh.name,
+        props,
+        paths,
+        save_v_norms=False,
+        store_usd=False,  # NOTE: False for fast simulation!
+        optimize_storage=False,  # props['sim']['config']['optimize_storage'],
+        verbose=False
+    )
+
+    props.serialize(paths.element_sim_props)
+
+
+def modelandreturn_picture_path(input_json):
+
+    ''' If you simulate a json file, you will save a folder in the directory where the json file is located, removing the specifiction ending as the folder name.
+    Contains all the information for the simulation and returns the path to the simulation from the front perspective
+    Args:
+        input_json (string): A json file that needs to be mocked
+    Responds:
+        image_path2 (string): the path of the simulation map in the front view.
+
+    '''
+
+    json2modelfolder(input_json)
+    input_json=Path(input_json)
+    input_folder=input_json.parent
+    garment_name, _, _ = input_json.stem.rpartition('_')
+    image_path2=input_folder / garment_name / f"{str(garment_name)}_render_front.png"
+
+    return image_path2