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Support --save-pk in demo_video_x.py #170

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Support --save-pk in demo_video_x.py #170

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90 changes: 44 additions & 46 deletions scripts/demo_video_x.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
"""Image demo script."""
import argparse
import os
import pickle as pk

import cv2
import numpy as np
Expand Down Expand Up @@ -129,7 +130,7 @@ def integral_hm(hms):
help='output folder',
default='',
type=str)
parser.add_argument('--save-pt', default=False, dest='save_pt',
parser.add_argument('--save-pk', default=False, dest='save_pk',
help='save prediction', action='store_true')
parser.add_argument('--save-img', default=False, dest='save_img',
help='save prediction', action='store_true')
Expand Down Expand Up @@ -158,19 +159,16 @@ def integral_hm(hms):

res_keys = [
'pred_uvd',
'pred_xyz_17',
'pred_xyz_29',
'pred_xyz_24_struct',
'pred_scores',
'pred_camera',
'f',
'pred_betas',
'pred_thetas',
'pred_phi',
'scale_mult',
'pred_cam_root',
# 'features',
'transl',
'transl_camsys',
'bbox',
'height',
'width',
Expand Down Expand Up @@ -337,6 +335,8 @@ def integral_hm(hms):
image = input_image.copy()
focal = 1000.0
bbox_xywh = xyxy2xywh(bbox)
transl_camsys = transl.clone()
transl_camsys = transl_camsys * 256 / bbox_xywh[2]

focal = focal / 256 * bbox_xywh[2]

Expand Down Expand Up @@ -384,48 +384,46 @@ def integral_hm(hms):
res_path = os.path.join(
opt.out_dir, 'res_2d_images', f'image-{idx:06d}.jpg')
cv2.imwrite(res_path, bbox_img)

if opt.save_pt:
assert pose_input.shape[0] == 1, 'Only support single batch inference for now'

pred_xyz_jts_17 = pose_output.pred_xyz_jts_17.reshape(
17, 3).cpu().data.numpy()
pred_uvd_jts = pose_output.pred_uvd_jts.reshape(
-1, 3).cpu().data.numpy()
pred_xyz_jts_29 = pose_output.pred_xyz_jts_29.reshape(
-1, 3).cpu().data.numpy()
pred_xyz_jts_24_struct = pose_output.pred_xyz_jts_24_struct.reshape(
24, 3).cpu().data.numpy()
pred_scores = pose_output.maxvals.cpu(
).data[:, :29].reshape(29).numpy()
pred_camera = pose_output.pred_camera.squeeze(
dim=0).cpu().data.numpy()
pred_betas = pose_output.pred_shape.squeeze(
dim=0).cpu().data.numpy()
pred_theta = pose_output.pred_theta_mats.squeeze(
dim=0).cpu().data.numpy()
pred_phi = pose_output.pred_phi.squeeze(dim=0).cpu().data.numpy()
pred_cam_root = pose_output.cam_root.squeeze(dim=0).cpu().numpy()
img_size = np.array((input_image.shape[0], input_image.shape[1]))

res_db['pred_xyz_17'].append(pred_xyz_jts_17)
res_db['pred_uvd'].append(pred_uvd_jts)
res_db['pred_xyz_29'].append(pred_xyz_jts_29)
res_db['pred_xyz_24_struct'].append(pred_xyz_jts_24_struct)
res_db['pred_scores'].append(pred_scores)
res_db['pred_camera'].append(pred_camera)
res_db['f'].append(1000.0)
res_db['pred_betas'].append(pred_betas)
res_db['pred_thetas'].append(pred_theta)
res_db['pred_phi'].append(pred_phi)
res_db['pred_cam_root'].append(pred_cam_root)
# res_db['features'].append(img_feat)
res_db['transl'].append(transl[0].cpu().data.numpy())
res_db['bbox'].append(np.array(bbox))
res_db['height'].append(img_size[0])
res_db['width'].append(img_size[1])
res_db['img_path'].append(img_path)
'''
if opt.save_pk:
assert pose_input.shape[0] == 1, 'Only support single batch inference for now'
pred_uvd_jts = pose_output.pred_uvd_jts.reshape(
-1, 3).cpu().data.numpy()
pred_scores = pose_output.maxvals.cpu(
).data[:, :29].reshape(29).numpy()
pred_camera = pose_output.pred_camera.squeeze(
dim=0).cpu().data.numpy()
pred_betas = pose_output.pred_shape_full.squeeze(
dim=0).cpu().data.numpy()
pred_theta = pose_output.pred_theta_mat.squeeze(
dim=0).cpu().data.numpy()
pred_phi = pose_output.pred_phi.squeeze(dim=0).cpu().data.numpy()
pred_cam_root = pose_output.cam_root.squeeze(dim=0).cpu().numpy()
img_size = np.array((input_image.shape[0], input_image.shape[1]))

res_db['pred_uvd'].append(pred_uvd_jts)
res_db['pred_scores'].append(pred_scores)
res_db['pred_camera'].append(pred_camera)
res_db['f'].append(1000.0)
res_db['pred_betas'].append(pred_betas)
res_db['pred_thetas'].append(pred_theta)
res_db['pred_phi'].append(pred_phi)
res_db['pred_cam_root'].append(pred_cam_root)
res_db['transl'].append(transl[0].cpu().data.numpy())
res_db['transl_camsys'].append(transl_camsys[0].cpu().data.numpy())
res_db['bbox'].append(np.array(bbox))
res_db['height'].append(img_size[0])
res_db['width'].append(img_size[1])
res_db['img_path'].append(img_path)

if opt.save_pk:
n_frames = len(res_db['img_path'])
for k in res_db.keys():
res_db[k] = np.stack(res_db[k])
assert res_db[k].shape[0] == n_frames

with open(os.path.join(opt.out_dir, 'res.pk'), 'wb') as fid:
pk.dump(res_db, fid)

write_stream.release()
write2d_stream.release()