Food – 101 Dataset 是包含 101 种食品类别的图像数据集,主要用于图像分类,共有 101,000 张图像,每个类别的测试图像和训练图像分别有 250 张和 750 张,其中训练图像未经数据清洗,但所有图像均以重新进行尺寸缩放,最大边长在 512 像素。 该数据集由斯坦福大学于 2014 年发布,相关论文有《Food-101 — Mining Di...
The Food-101 dataset consists of 101 food categories with 750 training and 250 test images per category, making a total of 101k images. The labels for the test images have been manually cleaned, while the training set contains some noise. Source: Combining Weakly and Webly Supervised Learning...
Food101数据集,包含101类食物 在AI界浑水摸鱼 8枚 CC0 图像分类计算机视觉 2 8 2022-12-09 详情 相关项目 评论(0) 创建项目 文件列表 food-101.zip food-101.zip (5430.11M) 下载 File Name Size Update Time classes.txt 1184 2014-07-09 21:04:28 h5/food_c101_n1000_r384x384x3.h5 359407496 ...
(train, val, test, self.split_path, self.image_dir) num_shots = cfg.DATASET.NUM_SHOTS if num_shots >= 1: seed = cfg.SEED preprocessed = os.path.join(self.split_fewshot_dir, f"shot_{num_shots}-seed_{seed}.pkl") if os.path.exists(preprocessed): print(f"Loading preprocessed few...
To measure the performance of our rf component mining for food recognition, we introduce a novel and challenging dataset of 101 food categories, with 101'000 images. With an average accuracy of 50.76%, our model outperforms alternative classification methods except for cnn, including svm ...
The base model is EfficientNetB1 which has been originally trained on ImageNet dataset. We use the power of transfer learning and fine-tuning to achieve accuracy of 80%. We also receive the bonus point because our model training was over in a couple of minutes compared to the mentioned 2-...
To measure the performance of our rf component mining for food recognition, we introduce a novel and challenging dataset of 101 food categories, with 101'000 images. With an average accuracy of 50.76%, our model outperforms alternative classification methods except for CNN, including SVM ...
we introduce a novel and challenging dataset of 101 food categories, with 101’000 images. With an average accuracy of 50.76%, our model outperforms alternative classification methods except for cnn, including svm classification on Improved Fisher Vectors and existing discriminative part-mining algorithm...
h.create_dataset('data', data=X_test) h.create_dataset('classes', data=y_test_cat) h.close() ### Set up Image Augmentation print("Setting up ImageDataGenerator") datagen = ImageDataGenerator( featurewise_center=False, # set input mean to 0 over the dataset samplewise_center=False, #...
This is the Food101 dataset implemented in Apple's new framework called CoreML. The Food101 dataset can predict foods from images. The model was built with Keras 1.2.2 and is a fine-tuned InceptionV3 model. To test this model you can open the Food101Prediction.xcodeproj and run it on ...