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🐞 Fix inferencer in Gradio #332

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merged 3 commits into from
May 25, 2022
Merged

🐞 Fix inferencer in Gradio #332

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c915019
Fix inferencer in gradio
ashwinvaidya17 May 24, 2022
02537c7
Adddress PR comments
ashwinvaidya17 May 24, 2022
063477b
Address PR comments
ashwinvaidya17 May 24, 2022
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29 changes: 11 additions & 18 deletions tools/inference_gradio.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@
from argparse import ArgumentParser, Namespace
from importlib import import_module
from pathlib import Path
from typing import Optional, Tuple, Union
from typing import Optional, Tuple

import gradio as gr
import gradio.inputs
Expand Down Expand Up @@ -47,16 +47,15 @@ def get_args() -> Namespace:

Example:

>>> python tools/inference_gradio.py --model ./anomalib/models/padim/config.yaml --weight_path ./results/padim/mvtec/bottle/weights/model.ckpt
>>> python tools/inference_gradio.py --model padim --weight_path ./results/padim/mvtec/bottle/weights/model.ckpt
>>> python tools/inference_gradio.py \
--config ./anomalib/models/padim/config.yaml \
--weight_path ./results/padim/mvtec/bottle/weights/model.ckpt

Returns:
Namespace: List of arguments.
"""
parser = ArgumentParser()
parser.add_argument(
"--model", type=str, required=True, help="Can be either the model name or the path to a model config file"
)
parser.add_argument("--config", type=Path, required=True, help="Path to a model config file")
parser.add_argument("--weight_path", type=Path, required=True, help="Path to a model weights")
parser.add_argument("--meta_data", type=Path, required=False, help="Path to JSON file containing the metadata.")
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there is a bit of inconsistency in naming. In fact, this is the case for other entrypoints. I think we should stick to one of the following

- config, weights, meta_data
- config_path, weight_path, meta_data_path

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That's alright. The whole point of the review is to ensure code quality


Expand All @@ -72,14 +71,10 @@ def get_args() -> Namespace:

args = parser.parse_args()

# Model config is passed as the input argument else assume that model name is passed to model
if args.model.endswith(".yaml"):
args.model = Path(args.model)

return args


def get_inferencer(model: Union[Path, str], weight_path: Path, meta_data_path: Optional[Path] = None) -> Inferencer:
def get_inferencer(config_path: Path, weight_path: Path, meta_data_path: Optional[Path] = None) -> Inferencer:
"""Parse args and open inferencer.

Args:
Expand All @@ -93,22 +88,20 @@ def get_inferencer(model: Union[Path, str], weight_path: Path, meta_data_path: O
Returns:
Inferencer: Torch or OpenVINO inferencer.
"""
if isinstance(model, Path):
config = get_configurable_parameters(config_path=model)
else:
config = get_configurable_parameters(model_name=model)
config = get_configurable_parameters(config_path=config_path)

# Get the inferencer. We use .ckpt extension for Torch models and (onnx, bin)
# for the openvino models.
extension = weight_path.suffix
inferencer: Inferencer
if extension in (".ckpt"):
module = import_module("anomalib.deploy.inferencers.torch")
TorchInferencer = getattr(module, "TorchInferencer") # pylint: disable=invalid-name
TorchInferencer = getattr(module, "TorchInferencer")
inferencer = TorchInferencer(config=config, model_source=weight_path, meta_data_path=meta_data_path)

elif extension in (".onnx", ".bin", ".xml"):
module = import_module("anomalib.deploy.inferencers.openvino")
OpenVINOInferencer = getattr(module, "OpenVINOInferencer") # pylint: disable=invalid-name
OpenVINOInferencer = getattr(module, "OpenVINOInferencer")
inferencer = OpenVINOInferencer(config=config, path=weight_path, meta_data_path=meta_data_path)

else:
Expand All @@ -123,7 +116,7 @@ def get_inferencer(model: Union[Path, str], weight_path: Path, meta_data_path: O
if __name__ == "__main__":
session_args = get_args()

gradio_inferencer = get_inferencer(session_args.model, session_args.weight_path, session_args.meta_data)
gradio_inferencer = get_inferencer(session_args.config, session_args.weight_path, session_args.meta_data)

interface = gr.Interface(
fn=lambda image, threshold: infer(image, gradio_inferencer, threshold),
Expand Down