<commit_before>import argparse

import cv2
import torch

from mmdet.apis import inference_detector, init_detector, show_result


def parse_args():
    parser = argparse.ArgumentParser(description='MMDetection webcam demo')
    parser.add_argument('config', help='test config file path')
    parser.add_argument('checkpoint', help='checkpoint file')
    parser.add_argument('--device', type=int, default=0, help='CUDA device id')
    parser.add_argument(
        '--camera-id', type=int, default=0, help='camera device id')
    parser.add_argument(
        '--score-thr', type=float, default=0.5, help='bbox score threshold')
    args = parser.parse_args()
    return args


def main():
    args = parse_args()

    model = init_detector(
        args.config, args.checkpoint, device=torch.device('cuda', args.device))

    camera = cv2.VideoCapture(args.camera_id)

    while True:
        ret_val, img = camera.read()
        result = inference_detector(model, img)
        show_result(
            img, result, model.CLASSES, score_thr=args.score_thr, wait_time=1)<commit_msg>Press key to exit (#1155)<commit_after>import argparse

import cv2
import torch

from mmdet.apis import inference_detector, init_detector, show_result


def parse_args():
    parser = argparse.ArgumentParser(description='MMDetection webcam demo')
    parser.add_argument('config', help='test config file path')
    parser.add_argument('checkpoint', help='checkpoint file')
    parser.add_argument('--device', type=int, default=0, help='CUDA device id')
    parser.add_argument(
        '--camera-id', type=int, default=0, help='camera device id')
    parser.add_argument(
        '--score-thr', type=float, default=0.5, help='bbox score threshold')
    args = parser.parse_args()
    return args


def main():
    args = parse_args()

    model = init_detector(
        args.config, args.checkpoint, device=torch.device('cuda', args.device))

    camera = cv2.VideoCapture(args.camera_id)

    print('Press "Esc", "q" or "Q" to exit.')
    while True:
        ret_val, img = camera.read()
        result = inference_detector(model, img)

        ch = cv2.waitKey(1)
        if ch == 27 or ch == ord('q') or ch == ord('Q'):
            break

        show_result(
            img, result, model.CLASSES, score_thr=args.score_thr, wait_time=1)
{'fraction_non_alphanumeric': 0.12850366537300562, 'fraction_numerical': 0.009486847779215178, 'mean_word_length': 3.5136186770428015, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '3059218', 'n_tokens_mistral': 752, 'n_tokens_neox': 725, 'n_words': 174}