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import lmdb |
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import os |
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import numpy as np |
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import cv2 as cv |
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from tqdm import tqdm |
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class IIIT5K: |
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def __init__(self, root): |
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self.root = root |
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self.acc = -1 |
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self.inputSize = [100, 32] |
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self.val_label = self.load_label(self.root) |
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@property |
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def name(self): |
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return self.__class__.__name__ |
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def load_label(self, root): |
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lmdb_file = root |
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lmdb_env = lmdb.open(lmdb_file) |
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lmdb_txn = lmdb_env.begin() |
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lmdb_cursor = lmdb_txn.cursor() |
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label = list() |
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for key, value in lmdb_cursor: |
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image_index = key.decode() |
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if image_index.split('-')[0] == 'image': |
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img = cv.imdecode(np.fromstring(value, np.uint8), 3) |
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label_index = 'label-' + image_index.split('-')[1] |
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value = lmdb_txn.get(label_index.encode()).decode().lower() |
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label.append([img, value]) |
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else: |
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break |
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return label |
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def eval(self, model): |
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right_num = 0 |
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pbar = tqdm(self.val_label) |
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pbar.set_description("Evaluating {} with {} val set".format(model.name, self.name)) |
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for img, value in pbar: |
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rbbox = np.array([0, img.shape[0], 0, 0, img.shape[1], 0, img.shape[1], img.shape[0]]) |
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pred = model.infer(img, rbbox).lower() |
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if value == pred: |
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right_num += 1 |
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self.acc = right_num/(len(self.val_label) * 1.0) |
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def get_result(self): |
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return self.acc |
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def print_result(self): |
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print("Accuracy: {:.2f}%".format(self.acc*100)) |
