import pandas as pd import numpy as np from PIL import Image import onnxruntime as ort import os from tqdm import tqdm def is_gpu_available(): """Check if the python package `onnxruntime-gpu` is installed.""" return ort.get_device() == "GPU" class ONNXWorker: """Run inference using ONNX runtime.""" def __init__(self, onnx_path: str): print("Setting up ONNX runtime session.") self.use_gpu = is_gpu_available() if self.use_gpu: providers = ["CUDAExecutionProvider", "CPUExecutionProvider"] else: providers = ["CPUExecutionProvider"] print(f"Using {providers}") self.ort_session = ort.InferenceSession(onnx_path, providers=providers) def _resize_image(self, image: np.ndarray) -> np.ndarray: new_size = (384, 384) return np.array(Image.fromarray(image).resize(new_size)) def predict_image(self, image: np.ndarray) -> list(): """Run inference using ONNX runtime.""" resized_image = self._resize_image(image) logits = self.ort_session.run(None, {"input": resized_image}) return logits.tolist() def make_submission(test_metadata, model_path, output_csv_path="./submission.csv", images_root_path="/tmp/data/private_testset"): """Make submission with given """ model = ONNXWorker(model_path) predictions = [] for _, row in tqdm(test_metadata.iterrows(), total=len(test_metadata)): image_path = os.path.join(images_root_path, row.filename) test_image = Image.open(image_path).convert("RGB") test_image_resized = np.asarray(test_image.resize((384, 384))) logits = model.predict_image(test_image_resized) predictions.append(np.argmax(logits)) test_metadata["class_id"] = predictions user_pred_df = test_metadata.drop_duplicates("observation_id", keep="first") user_pred_df[["observation_id", "class_id"]].to_csv(output_csv_path, index=None) if __name__ == "__main__": import zipfile with zipfile.ZipFile("/tmp/data/private_testset.zip", 'r') as zip_ref: zip_ref.extractall("/tmp/data") ONNX_MODEL_PATH = "./MetaFG_meta_2.onnx" metadata_file_path = "./SnakeCLEF2024-TestMetadata.csv" test_metadata = pd.read_csv(metadata_file_path) make_submission( test_metadata=test_metadata, model_path=ONNX_MODEL_PATH, )