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| # Copyright (c) Facebook, Inc. and its affiliates. | |
| import argparse | |
| import glob | |
| import multiprocessing as mp | |
| import numpy as np | |
| import os | |
| import tempfile | |
| import time | |
| import warnings | |
| import cv2 | |
| import tqdm | |
| import sys | |
| from detectron2.config import get_cfg | |
| from detectron2.data.detection_utils import read_image | |
| from detectron2.utils.logger import setup_logger | |
| sys.path.insert(0, 'third_party/CenterNet2/projects/CenterNet2/') | |
| from centernet.config import add_centernet_config | |
| from detic.config import add_detic_config | |
| from detic.predictor import VisualizationDemo | |
| # constants | |
| WINDOW_NAME = "Detic" | |
| def setup_cfg(args): | |
| cfg = get_cfg() | |
| add_centernet_config(cfg) | |
| add_detic_config(cfg) | |
| cfg.merge_from_file(args.config_file) | |
| cfg.merge_from_list(args.opts) | |
| # Set score_threshold for builtin models | |
| cfg.MODEL.RETINANET.SCORE_THRESH_TEST = args.confidence_threshold | |
| cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = args.confidence_threshold | |
| cfg.MODEL.PANOPTIC_FPN.COMBINE.INSTANCES_CONFIDENCE_THRESH = args.confidence_threshold | |
| cfg.MODEL.ROI_BOX_HEAD.ZEROSHOT_WEIGHT_PATH = 'rand' # load later | |
| if not args.pred_all_class: | |
| cfg.MODEL.ROI_HEADS.ONE_CLASS_PER_PROPOSAL = True | |
| cfg.freeze() | |
| return cfg | |
| def get_parser(): | |
| parser = argparse.ArgumentParser(description="Detectron2 demo for builtin configs") | |
| parser.add_argument( | |
| "--config-file", | |
| default="configs/quick_schedules/mask_rcnn_R_50_FPN_inference_acc_test.yaml", | |
| metavar="FILE", | |
| help="path to config file", | |
| ) | |
| parser.add_argument("--webcam", action="store_true", help="Take inputs from webcam.") | |
| parser.add_argument("--video-input", help="Path to video file.") | |
| parser.add_argument( | |
| "--input", | |
| nargs="+", | |
| help="A list of space separated input images; " | |
| "or a single glob pattern such as 'directory/*.jpg'", | |
| ) | |
| parser.add_argument( | |
| "--output", | |
| help="A file or directory to save output visualizations. " | |
| "If not given, will show output in an OpenCV window.", | |
| ) | |
| parser.add_argument( | |
| "--vocabulary", | |
| default="lvis", | |
| choices=['lvis', 'openimages', 'objects365', 'coco', 'custom'], | |
| help="", | |
| ) | |
| parser.add_argument( | |
| "--custom_vocabulary", | |
| default="", | |
| help="", | |
| ) | |
| parser.add_argument("--pred_all_class", action='store_true') | |
| parser.add_argument( | |
| "--confidence-threshold", | |
| type=float, | |
| default=0.5, | |
| help="Minimum score for instance predictions to be shown", | |
| ) | |
| parser.add_argument( | |
| "--opts", | |
| help="Modify config options using the command-line 'KEY VALUE' pairs", | |
| default=[], | |
| nargs=argparse.REMAINDER, | |
| ) | |
| return parser | |
| def test_opencv_video_format(codec, file_ext): | |
| with tempfile.TemporaryDirectory(prefix="video_format_test") as dir: | |
| filename = os.path.join(dir, "test_file" + file_ext) | |
| writer = cv2.VideoWriter( | |
| filename=filename, | |
| fourcc=cv2.VideoWriter_fourcc(*codec), | |
| fps=float(30), | |
| frameSize=(10, 10), | |
| isColor=True, | |
| ) | |
| [writer.write(np.zeros((10, 10, 3), np.uint8)) for _ in range(30)] | |
| writer.release() | |
| if os.path.isfile(filename): | |
| return True | |
| return False | |
| if __name__ == "__main__": | |
| mp.set_start_method("spawn", force=True) | |
| args = get_parser().parse_args() | |
| setup_logger(name="fvcore") | |
| logger = setup_logger() | |
| logger.info("Arguments: " + str(args)) | |
| cfg = setup_cfg(args) | |
| demo = VisualizationDemo(cfg, args) | |
| if args.input: | |
| if len(args.input) == 1: | |
| args.input = glob.glob(os.path.expanduser(args.input[0])) | |
| assert args.input, "The input path(s) was not found" | |
| for path in tqdm.tqdm(args.input, disable=not args.output): | |
| img = read_image(path, format="BGR") | |
| start_time = time.time() | |
| predictions, visualized_output = demo.run_on_image(img) | |
| logger.info( | |
| "{}: {} in {:.2f}s".format( | |
| path, | |
| "detected {} instances".format(len(predictions["instances"])) | |
| if "instances" in predictions | |
| else "finished", | |
| time.time() - start_time, | |
| ) | |
| ) | |
| if args.output: | |
| if os.path.isdir(args.output): | |
| assert os.path.isdir(args.output), args.output | |
| out_filename = os.path.join(args.output, os.path.basename(path)) | |
| else: | |
| assert len(args.input) == 1, "Please specify a directory with args.output" | |
| out_filename = args.output | |
| visualized_output.save(out_filename) | |
| else: | |
| cv2.namedWindow(WINDOW_NAME, cv2.WINDOW_NORMAL) | |
| cv2.imshow(WINDOW_NAME, visualized_output.get_image()[:, :, ::-1]) | |
| if cv2.waitKey(0) == 27: | |
| break # esc to quit | |
| elif args.webcam: | |
| assert args.input is None, "Cannot have both --input and --webcam!" | |
| assert args.output is None, "output not yet supported with --webcam!" | |
| cam = cv2.VideoCapture(0) | |
| for vis in tqdm.tqdm(demo.run_on_video(cam)): | |
| cv2.namedWindow(WINDOW_NAME, cv2.WINDOW_NORMAL) | |
| cv2.imshow(WINDOW_NAME, vis) | |
| if cv2.waitKey(1) == 27: | |
| break # esc to quit | |
| cam.release() | |
| cv2.destroyAllWindows() | |
| elif args.video_input: | |
| video = cv2.VideoCapture(args.video_input) | |
| width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH)) | |
| height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT)) | |
| frames_per_second = video.get(cv2.CAP_PROP_FPS) | |
| num_frames = int(video.get(cv2.CAP_PROP_FRAME_COUNT)) | |
| basename = os.path.basename(args.video_input) | |
| codec, file_ext = ( | |
| ("x264", ".mkv") if test_opencv_video_format("x264", ".mkv") else ("mp4v", ".mp4") | |
| ) | |
| if codec == ".mp4v": | |
| warnings.warn("x264 codec not available, switching to mp4v") | |
| if args.output: | |
| if os.path.isdir(args.output): | |
| output_fname = os.path.join(args.output, basename) | |
| output_fname = os.path.splitext(output_fname)[0] + file_ext | |
| else: | |
| output_fname = args.output | |
| assert not os.path.isfile(output_fname), output_fname | |
| output_file = cv2.VideoWriter( | |
| filename=output_fname, | |
| # some installation of opencv may not support x264 (due to its license), | |
| # you can try other format (e.g. MPEG) | |
| fourcc=cv2.VideoWriter_fourcc(*codec), | |
| fps=float(frames_per_second), | |
| frameSize=(width, height), | |
| isColor=True, | |
| ) | |
| assert os.path.isfile(args.video_input) | |
| for vis_frame in tqdm.tqdm(demo.run_on_video(video), total=num_frames): | |
| if args.output: | |
| output_file.write(vis_frame) | |
| else: | |
| cv2.namedWindow(basename, cv2.WINDOW_NORMAL) | |
| cv2.imshow(basename, vis_frame) | |
| if cv2.waitKey(1) == 27: | |
| break # esc to quit | |
| video.release() | |
| if args.output: | |
| output_file.release() | |
| else: | |
| cv2.destroyAllWindows() | |