''' @ Date: 2021-01-12 17:12:50 @ Author: Qing Shuai @ LastEditors: Qing Shuai @ LastEditTime: 2021-01-14 17:14:34 @ FilePath: /EasyMocap/code/dataset/mv1pmf.py ''' import os import ipdb import torch from os.path import join import numpy as np import cv2 from .base import MVBase class MV1PMF(MVBase): def __init__(self, root, cams=[], pid=0, out=None, config={}, image_root='images', annot_root='annots', add_hand_face=True, undis=True, no_img=False) -> None: super().__init__(root, cams, out, config, image_root, annot_root, add_hand_face, undis, no_img) self.pid = pid def write_keypoints3d(self, keypoints3d, nf): results = [{'id': 0, 'keypoints3d': keypoints3d.tolist()}] self.writer.write_keypoints3d(results, nf) def write_smpl(self, params, nf, images=[], to_img=False): result = {'id': 0} result.update(params) self.writer.write_smpl([result], nf) def vis_smpl(self, vertices, faces, images, nf, sub_vis): render_data = {} if len(vertices.shape) == 3: vertices = vertices[0] pid = self.pid render_data[pid] = {'vertices': vertices, 'faces': faces, 'vid': pid, 'name': '{}_{}'.format(nf, pid)} cameras = {'K': [], 'R':[], 'T':[]} if len(sub_vis) == 0: sub_vis = self.cams for key in cameras.keys(): cameras[key] = [self.cameras[cam][key] for cam in sub_vis] images = [images[self.cams.index(cam)] for cam in sub_vis] self.writer.vis_smpl(render_data, nf, images, cameras) def vis_detections(self, images, annots, nf, to_img=True, sub_vis=[]): lDetections = [] for nv in range(len(images)): det = { 'id': self.pid, 'bbox': annots['bbox'][nv], 'keypoints': annots['keypoints'][nv] } lDetections.append([det]) if len(sub_vis) != 0: valid_idx = [self.cams.index(i) for i in sub_vis] images = [images[i] for i in valid_idx] lDetections = [lDetections[i] for i in valid_idx] return self.writer.vis_detections(images, lDetections, nf, key='keypoints', to_img=to_img, vis_id=False) def vis_repro(self, images, annots, kpts_repro, nf, to_img=True, sub_vis=[]): lDetections = [] for nv in range(len(images)): det = { 'id': -1, 'repro': kpts_repro[nv] } lDetections.append([det]) if len(sub_vis) != 0: valid_idx = [self.cams.index(i) for i in sub_vis] images = [images[i] for i in valid_idx] lDetections = [lDetections[i] for i in valid_idx] return self.writer.vis_detections(images, lDetections, nf, key='repro', to_img=to_img, vis_id=False) def __getitem__(self, index: int): images, annots_all = super().__getitem__(index) annots = {'bbox': [], 'keypoints': []} for nv, cam in enumerate(self.cams): data = [d for d in annots_all[nv] if d['id'] == self.pid] if len(data) == 1: data = data[0] bbox = data['bbox'] keypoints = data['keypoints'] else: print('not found pid {} in {}, {}'.format(self.pid, index, nv)) keypoints = np.zeros((25, 3)) bbox = np.array([0, 0, 100., 100., 0.]) annots['bbox'].append(bbox) annots['keypoints'].append(keypoints) for key in ['bbox', 'keypoints']: annots[key] = np.stack(annots[key]) return images, annots if __name__ == "__main__": root = '/home/qian/zjurv2/mnt/data/ftp/Human/vis/lightstage/CoreView_302_sync/' dataset = MV1PMF(root) images, annots = dataset[0]