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See https://github.com/quic/ai-hub-models/releases/v0.20.0 for changelog. Signed-off-by: QAIHM Team <[email protected]>
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| helmet | ||
| vest |
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| # --------------------------------------------------------------------- | ||
| # Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved. | ||
| # SPDX-License-Identifier: BSD-3-Clause | ||
| # --------------------------------------------------------------------- | ||
|
|
||
| from qai_hub_models.models._shared.depth_estimation.app import DepthEstimationApp | ||
| from qai_hub_models.utils.args import ( | ||
| demo_model_from_cli_args, | ||
| get_model_cli_parser, | ||
| get_on_device_demo_parser, | ||
| validate_on_device_demo_args, | ||
| ) | ||
| from qai_hub_models.utils.asset_loaders import CachedWebModelAsset, load_image | ||
| from qai_hub_models.utils.base_model import BaseModel | ||
| from qai_hub_models.utils.display import display_or_save_image | ||
|
|
||
|
|
||
| # The demo will display a heatmap of the estimated depth at each point in the image. | ||
| def depth_estimation_demo( | ||
| model_cls: type[BaseModel], | ||
| model_id, | ||
| default_image: CachedWebModelAsset, | ||
| is_test: bool = False, | ||
| ): | ||
| parser = get_model_cli_parser(model_cls) | ||
| parser = get_on_device_demo_parser(parser, add_output_dir=True) | ||
| parser.add_argument( | ||
| "--image", | ||
| type=str, | ||
| default=default_image, | ||
| help="image file path or URL", | ||
| ) | ||
| args = parser.parse_args([] if is_test else None) | ||
| model = demo_model_from_cli_args(model_cls, model_id, args) | ||
| validate_on_device_demo_args(args, model_id) | ||
|
|
||
| # Load image | ||
| (_, _, height, width) = model_cls.get_input_spec()["image"][0] | ||
| image = load_image(args.image) | ||
| print("Model Loaded") | ||
|
|
||
| app = DepthEstimationApp(model, height, width) | ||
| heatmap_image = app.estimate_depth(image) | ||
|
|
||
| if not is_test: | ||
| # Resize / unpad annotated image | ||
| display_or_save_image( | ||
| heatmap_image, args.output_dir, "out_heatmap.png", "heatmap" | ||
| ) |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,57 @@ | ||
| # --------------------------------------------------------------------- | ||
| # Copyright (c) 2024 Qualcomm Innovation Center, Inc. All rights reserved. | ||
| # SPDX-License-Identifier: BSD-3-Clause | ||
| # --------------------------------------------------------------------- | ||
| import json | ||
| from pathlib import Path | ||
|
|
||
| from qai_hub_models.models._shared.face_attrib_net.app import FaceAttribNetApp | ||
| from qai_hub_models.models.face_attrib_net.model import ( | ||
| MODEL_ASSET_VERSION, | ||
| MODEL_ID, | ||
| OUT_NAMES, | ||
| FaceAttribNet, | ||
| ) | ||
| from qai_hub_models.utils.args import ( | ||
| demo_model_from_cli_args, | ||
| get_model_cli_parser, | ||
| get_on_device_demo_parser, | ||
| validate_on_device_demo_args, | ||
| ) | ||
| from qai_hub_models.utils.asset_loaders import CachedWebModelAsset, load_image | ||
|
|
||
| INPUT_IMAGE_ADDRESS = CachedWebModelAsset.from_asset_store( | ||
| MODEL_ID, MODEL_ASSET_VERSION, "img_sample.bmp" | ||
| ) | ||
|
|
||
|
|
||
| # Run FaceAttribNet end-to-end on a sample image. | ||
| def face_attrib_net_demo(model_cls: type[FaceAttribNet], is_test: bool = False): | ||
| # Demo parameters | ||
| parser = get_model_cli_parser(model_cls) | ||
| parser = get_on_device_demo_parser(parser, add_output_dir=True) | ||
| parser.add_argument( | ||
| "--image", | ||
| type=str, | ||
| default=INPUT_IMAGE_ADDRESS, | ||
| help="image file path or URL", | ||
| ) | ||
| args = parser.parse_args([]) | ||
| model = demo_model_from_cli_args(model_cls, MODEL_ID, args) | ||
| validate_on_device_demo_args(args, MODEL_ID) | ||
|
|
||
| # Load image | ||
| _, _, height, width = model_cls.get_input_spec()["image"][0] | ||
| orig_image = load_image(args.image) | ||
| print("Model loaded") | ||
|
|
||
| app = FaceAttribNetApp(model) | ||
| output = app.run_inference_on_image(orig_image) | ||
| out_dict = {} | ||
| for i in range(len(output)): | ||
| out_dict[OUT_NAMES[i]] = list(output[i].astype(float)) | ||
|
|
||
| output_path = (args.output_dir or str(Path() / "build")) + "/output.json" | ||
| with open(output_path, "w", encoding="utf-8") as wf: | ||
| json.dump(out_dict, wf, ensure_ascii=False, indent=4) | ||
| print(f"Model outputs are saved at: {output_path}") |
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