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Merge pull request #3 from ShoufaChen/dev-demo
visualization demo
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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 | ||
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from detectron2.config import get_cfg | ||
from detectron2.data.detection_utils import read_image | ||
from detectron2.utils.logger import setup_logger | ||
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from diffusiondet.predictor import VisualizationDemo | ||
from diffusiondet import DiffusionDetDatasetMapper, add_diffusiondet_config, DiffusionDetWithTTA | ||
from diffusiondet.util.model_ema import add_model_ema_configs, may_build_model_ema, may_get_ema_checkpointer, EMAHook, \ | ||
apply_model_ema_and_restore, EMADetectionCheckpointer | ||
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# constants | ||
WINDOW_NAME = "COCO detections" | ||
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def setup_cfg(args): | ||
# load config from file and command-line arguments | ||
cfg = get_cfg() | ||
# To use demo for Panoptic-DeepLab, please uncomment the following two lines. | ||
# from detectron2.projects.panoptic_deeplab import add_panoptic_deeplab_config # noqa | ||
# add_panoptic_deeplab_config(cfg) | ||
add_diffusiondet_config(cfg) | ||
add_model_ema_configs(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.freeze() | ||
return cfg | ||
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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.", | ||
) | ||
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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 | ||
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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 | ||
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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)) | ||
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cfg = setup_cfg(args) | ||
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demo = VisualizationDemo(cfg) | ||
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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): | ||
# use PIL, to be consistent with evaluation | ||
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, | ||
) | ||
) | ||
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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() |
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