From 2b78d937695313adfbbec2fc7978a81b96f2c8e4 Mon Sep 17 00:00:00 2001 From: Hunor Laczko Date: Fri, 21 Oct 2022 22:36:14 +0000 Subject: [PATCH] verify cape skinning --- verify_cape_skinning.py | 166 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 166 insertions(+) create mode 100644 verify_cape_skinning.py diff --git a/verify_cape_skinning.py b/verify_cape_skinning.py new file mode 100644 index 0000000..d6773b8 --- /dev/null +++ b/verify_cape_skinning.py @@ -0,0 +1,166 @@ +import os + +import os +os.environ["CUDA_VISIBLE_DEVICES"] = '1' +import tensorflow as tf + +gpus = tf.config.experimental.list_physical_devices('GPU') +if gpus: + try: + # Currently, memory growth needs to be the same across GPUs + for gpu in gpus: + tf.config.experimental.set_memory_growth(gpu, True) + logical_gpus = tf.config.experimental.list_logical_devices('GPU') + print(len(gpus), "Physical GPUs,", len(logical_gpus), "Logical GPUs") + except RuntimeError as e: + # Memory growth must be set before GPUs have been initialized + print(e) + + +import sys +import time +import cv2 +import random +import numpy as np +import cmapy as cm +import plotly.graph_objects as go +import plotly.express as ex + +from dataset import DatasetFactory, StaticDataset +from custom_utils.custom_utils import batch_to_dict, UV2Mesh, _maskFaces +from custom_utils.smpl import SMPL + +if __name__ == '__main__': + + uv2mesh = UV2Mesh(is_smpl_orig=True) + smpl = SMPL(orig_smpl=True) + + F = np.load("custom_utils/smpl_faces_orig.npy") + + factory = DatasetFactory() + signature_dynamic = { 'id': (), + 'pose_shape': (72 + 11,), + # 'uv_posed': (3, 512, 256,), + # 'uv_body_posed': (3, 512, 256,), + 'mesh_body_posed': (3638, 3,), + 'mesh_posed': (3638, 3,), + 'mesh_unposed': (3638, 3,), + # 'uv_unposed': (3, 512, 256,), + # 'uv_curvature': (512, 256), + # 'mesh_curvature': (14475) + } + signature_static = { #'uv_static': (3, 512, 256,), + # 'mesh_static': (14475, 3,), + 'mesh_mask': (3638,), + # 'uv_mask': (512, 256,), + # 'uv_shaped_body': (3, 512, 256,), + } + + dataset = factory.get_dataset(folder='/home/workspace/local-data/cape_processed/train/female', + batch_size=1, + signature=signature_dynamic, + resolutions=[512], + is_cape=True) + static_dataset = StaticDataset(folder='/home/workspace/local-data/cape_processed/train/female', + signature=signature_static, + resolutions=[512], + is_cape=True) + + + + for i, batch in enumerate(dataset): + print(i) + batch = static_dataset.expand_batch(batch_to_dict(batch, signature_dynamic)) + + J0_old = np.load('custom_data/smpl_root_joint.npy') + + id = batch['id'][0].numpy().decode("utf-8") + mesh_unposed = np.squeeze(batch['mesh_unposed'].numpy()) + mask = np.squeeze(batch['mesh_mask'].numpy()).astype(bool) + pose, shape = batch['pose_shape'][:, :72].numpy(), batch['pose_shape'][:, 72:].numpy() + gender = tf.cast(tf.greater_equal(shape[:, 10] , 0.5), tf.int32) + shape_offsets = tf.stack([tf.gather(tf.tensordot(shape[i,:10][tf.newaxis, :], smpl.shapedirs[gender[i]], axes=[[1], [2]])[0,:,:], smpl.to_keep, axis=0) for i in range(shape.shape[0])]).numpy() + mesh_unposed_shaped = batch['mesh_unposed'] + shape_offsets * batch['mesh_mask'][:,:,tf.newaxis] + J0_new = smpl.run(smpl.run_rodrigues(np.zeros((1, 72), np.float32)), shape)[1][0,0,:].numpy() + + min_body = np.load(os.path.join('/home/workspace/local-data/temp/cape_release', 'minimal_body_shape', id.split('_')[0], id.split('_')[0] + '_minimal.npy'))[np.newaxis, :, :].astype(np.float32) + J0_2 = smpl.get_root_joint(shape, v_shaped=tf.stack([min_body, min_body], axis=-1))[0].numpy() + # min_body -= J0_2[np.newaxis,np.newaxis,:] + + mesh_unposed_shaped = mesh_unposed_shaped + J0_old[tf.newaxis,tf.newaxis,:] + mesh_reposed = smpl.run_garment(pose, shape, mesh_unposed_shaped, v_shaped=tf.stack([min_body, min_body], axis=-1)).numpy()[0] + mesh_posed = np.squeeze(batch['mesh_posed'].numpy()) + J0_old[np.newaxis,:] + mesh_body_posed_no_orient = np.squeeze(batch['mesh_body_posed'].numpy()) + mesh_body_posed = smpl.run(smpl.run_rodrigues(pose), shape)[0][0].numpy() + + # x = smpl.run(smpl.run_rodrigues(pose), shape)[0][0] + x = mesh_reposed[mask, :] + y = mesh_posed[mask, :] + _, faces = _maskFaces(np.zeros((3638, 3), dtype=np.float32), F, mask) + fig = go.Figure(data=[ + go.Mesh3d( + x=x[:,0], + y=x[:,1], + z=x[:,2], + i = faces[:,0], + j = faces[:,1], + k = faces[:,2] + ), + go.Mesh3d( + x=y[:,0], + y=y[:,1], + z=y[:,2], + i = faces[:,0], + j = faces[:,1], + k = faces[:,2] + ) + ]) + + + fig.update_layout(scene_aspectmode='manual', + scene_aspectratio=dict(x=1, y=1, z=1)) + fig.update_layout( + scene = dict( + xaxis = dict(nticks=4, range=[-1.5,1.5],), + yaxis = dict(nticks=4, range=[-1.5,1.5],), + zaxis = dict(nticks=4, range=[-1.5,1.5],),) + ) + + fig.show() + + + x = mesh_unposed_shaped.numpy()[0, mask, :] + # y = smpl.run(smpl.run_rodrigues(np.zeros((1, 72), np.float32)), shape)[0][0] + y = min_body[0, smpl.to_keep] + _, faces = _maskFaces(np.zeros((3638, 3), dtype=np.float32), F, mask) + fig = go.Figure(data=[ + go.Mesh3d( + x=x[:,0], + y=x[:,1], + z=x[:,2], + i = faces[:,0], + j = faces[:,1], + k = faces[:,2] + ), + go.Mesh3d( + x=y[:,0], + y=y[:,1], + z=y[:,2], + i = F[:,0], + j = F[:,1], + k = F[:,2] + ) + ]) + + fig.update_layout(scene_aspectmode='manual', + scene_aspectratio=dict(x=1, y=1, z=1)) + fig.update_layout( + scene = dict( + xaxis = dict(nticks=4, range=[-1.5,1.5],), + yaxis = dict(nticks=4, range=[-1.5,1.5],), + zaxis = dict(nticks=4, range=[-1.5,1.5],),) + ) + + fig.show() + + print() \ No newline at end of file