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demo.py
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# ---------------------------------------------------------------------
# Copyright (c) 2025 Qualcomm Technologies, Inc. and/or its subsidiaries.
# SPDX-License-Identifier: BSD-3-Clause
# ---------------------------------------------------------------------
from qai_hub_models.models.rtmpose_body2d.app import RTMPosebody2dApp
from qai_hub_models.models.rtmpose_body2d.model import (
MODEL_ASSET_VERSION,
MODEL_ID,
RTMPosebody2d,
)
from qai_hub_models.utils.args import (
demo_model_from_cli_args,
get_model_cli_parser,
get_on_device_demo_parser,
model_from_cli_args,
validate_on_device_demo_args,
)
from qai_hub_models.utils.asset_loaders import CachedWebModelAsset, load_image
from qai_hub_models.utils.display import display_or_save_image
IA_HELP_MSG = "More inferencer architectures for litehrnet can be found at https://github.com/open-mmlab/mmpose/tree/main/configs/body_2d_keypoint/topdown_heatmap/coco"
IMAGE_LOCAL_PATH = "rtmpose_demo_2.png"
IMAGE_ADDRESS = CachedWebModelAsset.from_asset_store(
MODEL_ID, MODEL_ASSET_VERSION, IMAGE_LOCAL_PATH
)
# Run RTMPose end-to-end on a sample image.
# The demo will display a image with the predicted keypoints.
def main(is_test: bool = False) -> None:
# Demo parameters
parser = get_model_cli_parser(RTMPosebody2d)
parser = get_on_device_demo_parser(parser, add_output_dir=True)
parser.add_argument(
"--image",
type=str,
default=IMAGE_ADDRESS,
help="image file path or URL",
)
args = parser.parse_args([] if is_test else None)
rtmpose_model = model_from_cli_args(RTMPosebody2d, args)
hub_model = demo_model_from_cli_args(RTMPosebody2d, MODEL_ID, args)
validate_on_device_demo_args(args, MODEL_ID)
# Load image & model
image = load_image(args.image)
print("Model Loaded")
app = RTMPosebody2dApp(
hub_model, # type: ignore[arg-type]
rtmpose_model.inferencer,
)
keypoints = app.predict_pose_keypoints(image)[0]
if not is_test:
display_or_save_image(
keypoints, args.output_dir, "rtmpose_body2d_demo_output.png"
)
if __name__ == "__main__":
main()