visualization/plot_3d_global.py

import torch 
import matplotlib.pyplot as plt
import numpy as np
import io
import os
import matplotlib
from PIL import Image
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
import mpl_toolkits.mplot3d.axes3d as p3
from textwrap import wrap
import imageio

def plot_3d_motion(args, figsize=(10, 10), fps=120, radius=4):
    matplotlib.use('Agg')

    joints, out_name, title = args
    
    data = joints.copy().reshape(len(joints), -1, 3)
    
    nb_joints = joints.shape[1]
    smpl_kinetic_chain = [[0, 11, 12, 13, 14, 15], [0, 16, 17, 18, 19, 20], [0, 1, 2, 3, 4], [3, 5, 6, 7], [3, 8, 9, 10]] if nb_joints == 21 else [[0, 2, 5, 8, 11], [0, 1, 4, 7, 10], [0, 3, 6, 9, 12, 15], [9, 14, 17, 19, 21], [9, 13, 16, 18, 20]]
    limits = 1000 if nb_joints == 21 else 2
    MINS = data.min(axis=0).min(axis=0)
    MAXS = data.max(axis=0).max(axis=0)
    colors = ['red', 'blue', 'black', 'red', 'blue',
              'darkblue', 'darkblue', 'darkblue', 'darkblue', 'darkblue',
              'darkred', 'darkred', 'darkred', 'darkred', 'darkred']
    frame_number = data.shape[0]
    #     print(data.shape)

    height_offset = MINS[1]
    data[:, :, 1] -= height_offset
    trajec = data[:, 0, [0, 2]]

    data[..., 0] -= data[:, 0:1, 0]
    data[..., 2] -= data[:, 0:1, 2]

    def update(index):

        def init():
            ax.set_xlim(-limits, limits)
            ax.set_ylim(-limits, limits)
            ax.set_zlim(0, limits)
            ax.grid(b=False)
        def plot_xzPlane(minx, maxx, miny, minz, maxz):
            ## Plot a plane XZ
            verts = [
                [minx, miny, minz],
                [minx, miny, maxz],
                [maxx, miny, maxz],
                [maxx, miny, minz]
            ]
            xz_plane = Poly3DCollection([verts])
            xz_plane.set_facecolor((0.5, 0.5, 0.5, 0.5))
            ax.add_collection3d(xz_plane)
        fig = plt.figure(figsize=(480/96., 320/96.), dpi=96) if nb_joints == 21 else plt.figure(figsize=(10, 10), dpi=96)
        if title is not None :
            wraped_title = '\n'.join(wrap(title, 40))
            fig.suptitle(wraped_title, fontsize=16)
        ax = p3.Axes3D(fig)
        
        init()
        
        # ax.lines = []
        # ax.collections = []

        ax.clear()  # Clear the axes instead of directly setting attributes

        ax.view_init(elev=110, azim=-90)
        ax.dist = 7.5
        #         ax =
        plot_xzPlane(MINS[0] - trajec[index, 0], MAXS[0] - trajec[index, 0], 0, MINS[2] - trajec[index, 1],
                     MAXS[2] - trajec[index, 1])
        #         ax.scatter(data[index, :22, 0], data[index, :22, 1], data[index, :22, 2], color='black', s=3)

        if index > 1:
            ax.plot3D(trajec[:index, 0] - trajec[index, 0], np.zeros_like(trajec[:index, 0]),
                      trajec[:index, 1] - trajec[index, 1], linewidth=1.0,
                      color='blue')
        #             ax = plot_xzPlane(ax, MINS[0], MAXS[0], 0, MINS[2], MAXS[2])

        for i, (chain, color) in enumerate(zip(smpl_kinetic_chain, colors)):
            #             print(color)
            if i < 5:
                linewidth = 4.0
            else:
                linewidth = 2.0
            ax.plot3D(data[index, chain, 0], data[index, chain, 1], data[index, chain, 2], linewidth=linewidth,
                      color=color)
        #         print(trajec[:index, 0].shape)

        plt.axis('off')
        ax.set_xticklabels([])
        ax.set_yticklabels([])
        ax.set_zticklabels([])

        io_buf = io.BytesIO()
        plt.savefig(io_buf, format='png', dpi=96)
        io_buf.seek(0)
        img = Image.open(io_buf)
        frame = np.array(img.convert('RGB'), dtype=np.uint8)
        io_buf.close()
        
        plt.close(fig)
        return frame
    
    out = []
    for i in range(frame_number):
        frame = update(i)
        if frame.ndim == 3 and frame.shape[2] == 3:
            out.append(frame)
        else:
            print(f"Frame {i} has incorrect shape or channels: {frame.shape}")
    return out

def draw_to_batch(smpl_joints_batch, title_batch=None, outname=None):
    batch_size = len(smpl_joints_batch)
    frames = []
    for i in range(batch_size):
        frames.extend(plot_3d_motion([smpl_joints_batch[i], None, title_batch[i] if title_batch is not None else None]))
    
    if frames:
        gif_bytes = io.BytesIO()
        imageio.mimsave(gif_bytes, frames, format='GIF', fps=120)
        gif_bytes.seek(0)
        gif_data = gif_bytes.getvalue()
        print(f"Generated GIF for batch size {batch_size}, size: {len(gif_data)} bytes")
        return gif_data
    else:
        print("No valid frames to generate GIF.")
        return None


    
#         if out_name is not None : 
#             plt.savefig(out_name, dpi=96)
#             plt.close()
            
#         else : 
#             io_buf = io.BytesIO()
#             fig.savefig(io_buf, format='raw', dpi=96)
#             io_buf.seek(0)
#             # print(fig.bbox.bounds)
#             arr = np.reshape(np.frombuffer(io_buf.getvalue(), dtype=np.uint8),
#                                 newshape=(int(fig.bbox.bounds[3]), int(fig.bbox.bounds[2]), -1))
#             io_buf.close()
#             plt.close()
#             return arr

#     out = []
#     for i in range(frame_number) : 
#         out.append(update(i))
#     out = np.stack(out, axis=0)
#     return torch.from_numpy(out)


# def draw_to_batch(smpl_joints_batch, title_batch=None, outname=None) : 
    
#     batch_size = len(smpl_joints_batch)
#     out = []
#     for i in range(batch_size) : 
#         out.append(plot_3d_motion([smpl_joints_batch[i], None, title_batch[i] if title_batch is not None else None]))
#         if outname is not None:
#             imageio.mimsave(outname[i], np.array(out[-1]), fps=20)
#     out = torch.stack(out, axis=0)
#     return out