import os
import sys


os.environ["CUDA_VISIBLE_DEVICES"] = '6'
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 glob
import tqdm
import copy
import numpy as np
from custom_utils.smpl import SMPL

# from custom_utils.custom_utils import UV2Mesh, _maskFaces
import plotly.graph_objects as go
# import plotly.express as ex
from scipy.spatial.transform import Rotation as R


if __name__ == '__main__':
    folder = '/home/workspace/local-data/test_skirt_ready'
    # folder = '/home/workspace/data/dataset/test_ready'
    # uv2mesh = UV2Mesh(is_skirt=False)
    smpl = SMPL(use_one_hot=False)

    F = np.load("custom_utils/smpl_faces.npy")

    ids = os.listdir(os.path.join(folder, 'pose_shape'))
    ids = [id.split('_')[0] for id in ids]
    ids = set(ids)
    os.makedirs(os.path.join(folder, 'mesh_posed_no_orient'), exist_ok=True)

    for id in tqdm.tqdm(ids):

        frames = glob.glob(os.path.join(folder, 'pose_shape', id + '_*'))
        frames = len(frames)

        mask = np.load(os.path.join(folder, 'mesh_mask', id + '.npy')).astype(bool)
        mesh_posed = [np.load(os.path.join(folder, 'mesh_posed',  id + '_' + str(i) + '.npz')) for i in range(frames)]
        mesh_posed = [mesh_posed[i]['mesh_posed'] for i in range(frames)]
        # mesh_unposed = [np.load(os.path.join(folder, 'mesh_unposed',  id + '_' + str(i) + '.npz')) for i in range(frames)]
        # mesh_unposed = [mesh_unposed[i]['mesh_unposed'] for i in range(frames)]
        pose_shape = [np.load(os.path.join(folder, 'pose_shape',  id + '_' + str(i) + '.npy')).astype(np.float32) for i in range(frames)]
        # pose_shape_no_orient = copy.deepcopy(pose_shape)
        # for i in range(len(pose_shape)):
        #     pose_shape_no_orient[i][:3] = 0

        rodr = smpl.run_rodrigues(np.stack([x[:72] for x in pose_shape]).astype(np.float32)).numpy()

        for frame in range(frames):
            r = R.from_matrix(rodr[frame, 0, :, :])
            # assert r.as_matrix() == rodr[frame, 0, :, :]
            out = r.apply(mesh_posed[frame], inverse=True)

            # x = smpl.run_garment(pose_shape_no_orient[frame][:72][np.newaxis,:], pose_shape_no_orient[frame][72:][np.newaxis,:], mesh_unposed[frame][np.newaxis,:,:])[0].numpy()[mask, :]
            # y = out[mask, :]
            # _, faces = _maskFaces(np.zeros((14475,3), 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=[-1,1],),
            #                     yaxis = dict(nticks=4, range=[-1,1],),
            #                     zaxis = dict(nticks=4, range=[-1,1],),)
            #                     )

            # fig.show()


            np.savez_compressed(os.path.join(folder, 'mesh_posed_no_orient', id + '_' + str(frame) + '.npz'), mesh_posed_no_orient=out)