Negative dimensions problem

Hi, with this code : ``` import sys import argparse import cv2 import yaml import os import time from FaceBoxes import FaceBoxes from TDDFA import TDDFA from utils.render import render from utils.depth import depth from utils.pncc import pncc from utils.uv import uv_tex from utils.pose import viz_pose from utils.serialization import ser_to_ply, ser_to_obj from utils.functions import draw_landmarks, get_suffix from utils.tddfa_util import str2bool def capture_from_webcam(cap, output_path): """Capture an image from the already opened webcam and save it to the specified path.""" ret, frame = cap.read() # Capture a single frame if not ret: print("Failed to capture image from webcam") return False # Save the captured frame to the specified path cv2.imwrite(output_path, frame) print(f"Image saved to {output_path}") return True def process_uv_map(args, webcam_image_path): """Process UV map generation from the captured image.""" cfg = yaml.load(open(args.config), Loader=yaml.SafeLoader) # Init FaceBoxes and TDDFA, recommend using onnx flag if args.onnx: os.environ['KMP_DUPLICATE_LIB_OK'] = 'True' os.environ['OMP_NUM_THREADS'] = '4' from FaceBoxes.FaceBoxes_ONNX import FaceBoxes_ONNX from TDDFA_ONNX import TDDFA_ONNX face_boxes = FaceBoxes_ONNX() tddfa = TDDFA_ONNX(**cfg) else: gpu_mode = args.mode == 'gpu' tddfa = TDDFA(gpu_mode=gpu_mode, **cfg) face_boxes = FaceBoxes() # Given a still image path and load to BGR channel img = cv2.imread(webcam_image_path) # Detect faces, get 3DMM params and roi boxes boxes = face_boxes(img) n = len(boxes) if n == 0: print(f'No face detected, skipping UV generation') return print(f'Detect {n} faces') param_lst, roi_box_lst = tddfa(img, boxes) # Visualization and serialization dense_flag = args.opt in ('2d_dense', '3d', 'depth', 'pncc', 'uv_tex', 'ply', 'obj') old_suffix = get_suffix(webcam_image_path) new_suffix = f'.{args.opt}' if args.opt in ('ply', 'obj') else '.jpg' wfp = f'examples/results/{webcam_image_path.split("/")[-1].replace(old_suffix, "")}_{args.opt}' + new_suffix ver_lst = tddfa.recon_vers(param_lst, roi_box_lst, dense_flag=dense_flag) if args.opt == '2d_sparse': draw_landmarks(img, ver_lst, show_flag=args.show_flag, dense_flag=dense_flag, wfp=wfp) elif args.opt == '2d_dense': draw_landmarks(img, ver_lst, show_flag=args.show_flag, dense_flag=dense_flag, wfp=wfp) elif args.opt == '3d': render(img, ver_lst, tddfa.tri, alpha=0.6, show_flag=args.show_flag, wfp=wfp) elif args.opt == 'depth': depth(img, ver_lst, tddfa.tri, show_flag=args.show_flag, wfp=wfp, with_bg_flag=True) elif args.opt == 'pncc': pncc(img, ver_lst, tddfa.tri, show_flag=args.show_flag, wfp=wfp, with_bg_flag=True) elif args.opt == 'uv_tex': uv_tex(img, ver_lst, tddfa.tri, show_flag=args.show_flag, wfp=wfp) elif args.opt == 'pose': viz_pose(img, param_lst, ver_lst, show_flag=args.show_flag, wfp=wfp) elif args.opt == 'ply': ser_to_ply(ver_lst, tddfa.tri, height=img.shape[0], wfp=wfp) elif args.opt == 'obj': ser_to_obj(img, ver_lst, tddfa.tri, height=img.shape[0], wfp=wfp) else: raise ValueError(f'Unknown opt {args.opt}') def main(args): webcam_image_path = 'C:/Users/benkl/OneDrive/Documents/face recognition/3DDFA_v2/examples/inputs/webcam_capture.jpg' # Open the webcam once cap = cv2.VideoCapture(0) if not cap.isOpened(): print("Cannot open webcam") sys.exit() try: while True: # Loop indefinitely print("Starting new capture session...") # Capture an image from the webcam (webcam stays open) if capture_from_webcam(cap, webcam_image_path): # Process UV map generation process_uv_map(args, webcam_image_path) else: print("Failed to capture image, retrying...") # Wait for 4 seconds before the next UV map generation print("Waiting for 4 seconds before next UV generation...") time.sleep(4) # 4 seconds delay except KeyboardInterrupt: print("Program terminated by user.") finally: # Release the webcam when done cap.release() if __name__ == '__main__': parser = argparse.ArgumentParser(description='The demo of still image of 3DDFA_V2 with continuous webcam capture') parser.add_argument('-c', '--config', type=str, default='C:/Users/benkl/OneDrive/Documents/face recognition/3DDFA_V2/configs/mb1_120x120.yml') parser.add_argument('-f', '--img_fp', type=str, default='C:/Users/benkl/OneDrive/Documents/face recognition/3DDFA_v2/examples/inputs/webcam_capture.jpg') parser.add_argument('-m', '--mode', type=str, default='gpu', help='gpu or cpu mode') parser.add_argument('-o', '--opt', type=str, default='uv_tex', choices=['2d_sparse', '2d_dense', '3d', 'depth', 'pncc', 'uv_tex', 'pose', 'ply', 'obj']) parser.add_argument('--show_flag', type=str2bool, default='true', help='whether to show the visualization result') parser.add_argument('--onnx', action='store_true', default=False) args = parser.parse_args() main(args) ``` i got : An error occurred during 3DDFA processing: negative dimensions are not allowed can someone tell me why ?