backend.py

import torch
import cv2
import numpy as np
from huggingface_hub import hf_hub_download
from nail_detection.main import get_nails

from DummyModel import load_dummy_model


class Infer():
    def __init__(self, DEBUG):
        self.model = load_dummy_model(DEBUG)

    def predict(self, data):
        nails = get_nails(cv2.cvtColor(data, cv2.COLOR_RGB2BGR))
        predictions = []
        if nails is None:
            predictions.append(-1)
            for _ in range(5):
                predictions.append(np.zeros((64, 64, 3)))
                predictions.append(-1)
        else:
            napsi_predictions = torch.argmax(self.model(nails), 1)
            napsi_sum = int(napsi_predictions.sum().detach().cpu())
            predictions.append(napsi_sum)
            for napsi_prediction, nail in zip(napsi_predictions, nails):
                predictions.append(nail)
                predictions.append(napsi_prediction)
        return predictions