import os
import sys
import time
import cv2
import random
import numpy as np
import tensorflow as tf
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__':
    os.environ["CUDA_VISIBLE_DEVICES"] = "6"

    uv2mesh = UV2Mesh()
    smpl = SMPL()

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

    factory = DatasetFactory()
    signature_dynamic = { 'id': (),
                          'pose_shape': (72 + 11,),
                        #   'uv_posed': (3, 512, 256,),
                        #   'uv_body_posed': (3, 512, 256,),
                          'mesh_body_posed': (14475, 3,),
                        #   'mesh_posed_body_no_orient': (14475, 3,),
                          'mesh_posed': (14475, 3,),
                          'mesh_unposed': (14475, 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': (14475,),
                        #  'uv_mask': (512, 256,),
                        #  'uv_shaped_body': (3, 512, 256,),
                          }

    dataset = factory.get_dataset(folder='/home/workspace/local-data/jumpsuit_test/train',
                                  batch_size=1,
                                  signature=signature_dynamic)
    static_dataset = StaticDataset(folder='/home/workspace/local-data/jumpsuit_test/train',
                                   signature=signature_static)


    uv_res = 256



    for i, batch in enumerate(dataset):
        print(i)
        batch = static_dataset.expand_batch(batch_to_dict(batch, signature_dynamic))

        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()
        mesh_reposed = smpl.run_garment(pose, shape, batch['mesh_unposed']).numpy()[0]
        mesh_posed = np.squeeze(batch['mesh_posed'].numpy())
        mesh_body_posed = np.squeeze(batch['mesh_body_posed'].numpy())
        mesh_posed_body_no_orient = np.squeeze(batch['mesh_posed_body_no_orient'].numpy())

        # x = mesh_posed[mask, :]
        R = smpl.run_rodrigues(pose)
        # shape[:, -1] = 1
        x = smpl.run(R, shape)[0][0]
        y = mesh_body_posed
        z = mesh_posed[mask, :]
        _, faces = _maskFaces(np.zeros((14475, 3), dtype=np.float32), F, mask)
        go.Figure(data=[
                go.Mesh3d(
                    # 8 vertices of a cube
                    x=x[:,0],
                    y=x[:,1],
                    z=x[:,2],
                    # i, j and k give the vertices of triangles
                    i = F[:,0],
                    j = F[:,1],
                    k = F[:,2]
                ),
                go.Mesh3d(
                    # 8 vertices of a cube
                    x=y[:,0],
                    y=y[:,1],
                    z=y[:,2],
                    # i, j and k give the vertices of triangles
                    i = F[:,0],
                    j = F[:,1],
                    k = F[:,2]
                ),
                # go.Mesh3d(
                #     # 8 vertices of a cube
                #     x=z[:,0],
                #     y=z[:,1],
                #     z=z[:,2],
                #     # i, j and k give the vertices of triangles
                #     i = faces[:,0],
                #     j = faces[:,1],
                #     k = faces[:,2]
                # ),
                ]).show()

        pose_2 = pose.copy()
        pose_2[:, :3] = 0
        R = smpl.run_rodrigues(pose_2)
        x = smpl.run(R, shape)[0][0]
        y = mesh_posed_body_no_orient
        _, faces = _maskFaces(np.zeros((14475, 3), dtype=np.float32), F, mask)
        go.Figure(data=[
                go.Mesh3d(
                    # 8 vertices of a cube
                    x=x[:,0],
                    y=x[:,1],
                    z=x[:,2],
                    # i, j and k give the vertices of triangles
                    i = F[:,0],
                    j = F[:,1],
                    k = F[:,2]
                ),
                go.Mesh3d(
                    # 8 vertices of a cube
                    x=y[:,0],
                    y=y[:,1],
                    z=y[:,2],
                    # i, j and k give the vertices of triangles
                    i = F[:,0],
                    j = F[:,1],
                    k = F[:,2]
                )]).show()

        x = mesh_posed[mask, :]
        y = mesh_reposed[mask, :]
        _, faces = _maskFaces(np.zeros((14475, 3), dtype=np.float32), F, mask)
        go.Figure(data=[
                go.Mesh3d(
                    # 8 vertices of a cube
                    x=x[:,0],
                    y=x[:,1],
                    z=x[:,2],
                    # i, j and k give the vertices of triangles
                    i = faces[:,0],
                    j = faces[:,1],
                    k = faces[:,2]
                ),
                go.Mesh3d(
                    # 8 vertices of a cube
                    x=y[:,0],
                    y=y[:,1],
                    z=y[:,2],
                    # i, j and k give the vertices of triangles
                    i = faces[:,0],
                    j = faces[:,1],
                    k = faces[:,2]
                )]).show()

        print()