# Copyright (c) Facebook, Inc. and its affiliates. ''' Modifications Copyright (c) 2024-present NAVER Corp, Apache License v2.0 original source: https://github.com/facebookresearch/Detic/blob/main/demo.py ''' 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 import mss from detectron2.config import get_cfg from detectron2.data.detection_utils import read_image from detectron2.utils.logger import setup_logger from detectron2.engine.defaults import _highlight sys.path.insert(0, 'third_party/CenterNet2/') from centernet.config import add_centernet_config from proxydet.config import add_proxydet_config from proxydet.predictor import VisualizationDemo # Fake a video capture object OpenCV style - half width, half height of first screen using MSS class ScreenGrab: def __init__(self): self.sct = mss.mss() m0 = self.sct.monitors[0] self.monitor = {'top': 0, 'left': 0, 'width': m0['width'] / 2, 'height': m0['height'] / 2} def read(self): img = np.array(self.sct.grab(self.monitor)) nf = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR) return (True, nf) def isOpened(self): return True def release(self): return True # constants WINDOW_NAME = "ProxyDet" def setup_cfg(args): cfg = get_cfg() if args.cpu: cfg.MODEL.DEVICE="cpu" add_centernet_config(cfg) add_proxydet_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", help="Take inputs from webcam.") parser.add_argument("--cpu", action='store_true', help="Use CPU only.") 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( "--zeroshot_weight_path", default=None, help="zeroshot text embedding path used during training", ) 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( "--base-cat-threshold", type=float, default=0.9, help="Minimum score for similarity with trained base categories", ) 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) print(_highlight(cfg.dump(), ".yaml")) 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!" if args.webcam == "screen": cam = ScreenGrab() else: cam = cv2.VideoCapture(int(args.webcam)) 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()