mirror of
https://github.com/gosticks/body-pose-animation.git
synced 2025-10-16 11:45:42 +00:00
72c2e60cfb
- update renderer (unify methods and simplify) - expose more configs to the yaml file - add interpolation to video - fix unstable camera while in video mode
217 lines
6.4 KiB
Python
217 lines
6.4 KiB
Python
from typing import List, Set, Dict, Tuple, Optional
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from utils.mapping import get_named_joints
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from renderer import DefaultRenderer, Renderer
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import numpy as np
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import cv2
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import yaml
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import os.path
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import glob
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from datetime import datetime
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def getfilename_from_conf(config, index=None, include_date=True):
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"""create a filename containing most training props
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Args:
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config ([type]): config object
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index ([type]): sample index
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"""
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name = ""
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if include_date:
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now = datetime.now()
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name += now.strftime("%d-%m-%H-%M")
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if index is not None:
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name = str(index).zfill(3) + "-"
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name = name + config['pose']['optimizer']
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name = name + "-lr[" + str(config['pose']['lr']) + "]"
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name = name + "-it[" + str(config['pose']['iterations']) + "]"
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if config['pose']['anglePrior']['enabled']:
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name = name + \
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"-ap[" + str(config['pose']['anglePrior']['weight']) + "]"
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if config['pose']['bodyPrior']['enabled']:
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name = name + "-bp[" + str(config['pose']['bodyPrior']['weight']) + "]"
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if config['pose']['angleSumLoss']['enabled']:
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name = name + \
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"-as[" + str(config['pose']['angleSumLoss']['weight']) + "]"
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if config['pose']['temporal']['enabled']:
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name = name + "-temporal"
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return name
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def get_output_path_from_conf(config, index=None):
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name = getfilename_from_conf(config, index=index)
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return os.path.join(config['output']['rootDir'], name)
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def load_config(name=None):
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if name is None:
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config_name_env = os.getenv('CONFIG_PATH')
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if config_name_env is not None:
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name = config_name_env
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else:
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name = './config.yaml'
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with open(name) as file:
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# The FullLoader parameter handles the conversion from YAML
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# scalar values to Python the dictionary format
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config = yaml.load(file, Loader=yaml.FullLoader)
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return config
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def get_torso(joints):
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"""get torso points from SMPL joint array
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Args:
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joints ([type]): SMPL joints array
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Returns:
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[type]: torso points array
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"""
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cam_est_joints_names = ["hip-left", "hip-right",
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"shoulder-left", "shoulder-right"]
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return get_named_joints(joints, cam_est_joints_names)
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def estimate_scale(joints, keypoints, pairs=[
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("shoulder-right", "hip-right"),
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("shoulder-left", "hip-left")
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], cam_fy=850):
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"""estimate image depth based on the height changes due to perspective.
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This method only provides a rough estimate by computing shoulder to hip distances
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between SMPL joints and OpenPose keypoints.
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Args:
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joints ([type]): List of all SMPL joints
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keypoints ([type]): List of all OpenPose keypoints
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cam_fy (int, optional): Camera Y focal length. Defaults to 850.
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"""
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# store distance vectors
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smpl_dists = []
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ops_dists = []
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for (j1, j2) in pairs:
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smpl_joints = get_named_joints(joints, [j1, j2])
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ops_keyp = get_named_joints(keypoints, [j1, j2])
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smpl_dists.append(smpl_joints[0] - smpl_joints[1])
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ops_dists.append(ops_keyp[0] - ops_keyp[1])
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smpl_height = np.linalg.norm(smpl_dists, axis=0).mean()
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ops_height = np.linalg.norm(ops_dists, axis=0).mean()
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return cam_fy / 1080 * smpl_height / ops_height
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def estimate_focal_length(run_estimation: bool = False):
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"""
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Estimate focal length by selecting a region of image whose real width is known.
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Executed once to compute a camera intrinsics matrix.
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For now, focal length = 850
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:return: focal_length
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"""
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# TODO: adjust known distances with more precise values if this method works
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if run_estimation:
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image = cv2.imread(os.path.dirname(__file__) + '/../samples/003.png')
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cv2.imshow("image", image)
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marker = cv2.selectROI(
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"image", image, fromCenter=False, showCrosshair=True)
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# width of the selected region (object) in the image
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region_width = marker[2]
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# known real distance from the camera to the object
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known_distance = 200
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# known real width of the object
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known_width = 50
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focal_length = (region_width * known_distance) / known_width
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print("Focal length:", focal_length)
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else:
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focal_length = 850
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return focal_length
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# Rename files, later save output of openpose to specific format so that this is not necessary
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def rename_files(dir):
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idx = 0
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counter = 0
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for x in os.listdir(dir):
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_, ext = x.split('.')
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try:
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os.rename(dir + x, dir + str(counter) + "." + ext)
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idx += 1
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if idx == 2:
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counter += 1
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idx = 0
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except FileExistsError:
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print("Files already renamed")
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break
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# Create a new filename by incrementing counter
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def get_new_filename():
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conf = load_config()
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results_dir = conf['output']['rootDir']
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result_prefix = conf['output']['prefix']
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results = glob.glob(results_dir + "*.pkl")
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if len(results) == 0:
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return result_prefix + "0.pkl"
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else:
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latest_file = max(results, key=os.path.getctime)
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num = int(latest_file.split("-")[1].split(".")[0])
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return result_prefix + str(num + 1) + ".pkl"
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def setup_training(model, dataset, sample_index, renderer=True, offscreen=False):
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keypoints, conf = dataset[sample_index]
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img_path = dataset.get_image_path(sample_index)
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# ---------------------------------
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# Generate model and get joints
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# ---------------------------------
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model_out = model()
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joints = model_out.joints.detach().cpu().numpy().squeeze()
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# ---------------------------------
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# Draw in the joints of interest
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# ---------------------------------
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est_scale = estimate_scale(joints, keypoints)
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# apply scaling to keypoints
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keypoints = keypoints * est_scale
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# integrating Camera Estimation
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init_joints = get_torso(joints)
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init_keypoints = get_torso(keypoints)
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r = None
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if renderer:
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# setup renderer
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r = DefaultRenderer(offscreen=offscreen)
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r.setup(
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model=model,
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model_out=model_out,
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keypoints=keypoints,
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init_keypoints=init_keypoints,
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init_joints=init_joints,
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img_path=img_path,
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img_scale=est_scale
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)
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return init_keypoints, init_joints, keypoints, conf, est_scale, r, img_path
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