Kaggle:https://www.kaggle.com/jangedoo/utkface-new dataset:https://susanqq.github.io/UTKFace/2 万张单人脸图片,覆盖 5 个人种,0-116 岁区间。原始数据 1.3GB,cropped 后 107MB。本文使用cropped后的数据集。 参考论文:Multi-digit Number Recognition from Street View Imagery using Deep Convolutional N...
"F": 6, "G": 7, "U": 8} data = [train_df, test_df] for dataset in data: dataset['Cabin'] = dataset['Cabin'].fillna("U0") dataset['Deck'] = dataset['Cabin'].map(lambda x: re.compile("([A-Z]+)").search(x).group()) dataset['Deck'] = dataset['Deck'].map(deck)...
Pytorch-Facial-Expression-Recognition This trained model recevies a colorful or grey image of an face and predicts emotion portrays in it. The availbe emotions are: Happy Sad Disgust Neutral Suprise Fear Angry In training of this model these resources and technologies were used: Pytorch framework ...
Additive Angular Margin Loss for Deep Face Recognition loss(损失)函数 损失函数也被称为成本函数或目标函数,它用来找出模型输出与目标输出之间的差异,并帮助模型最小化它们之间的距离。 下面是一些最流行的损失函数,以及一些项目示例,你可以从中找到一些技巧来提高模型容量: 标签平滑 焦loss 稀疏最大损失和加权...
gen_llm_car_free_v1.csv") lm_ali_4 = pd.read_csv("/kaggle/input/llm-dataset/gen_llm_exploring_venus_v1.csv") lm_ali_5 = pd.read_csv("/kaggle/input/llm-dataset/gen_llm_face_on_mars_v1.csv") lm_ali_6 = pd.read_csv("/kaggle/input/llm-dataset/gen_llm_driveless_cars_v1....
Essentially, instantiate a KaggleDatasets object, and from it search datasets, see their metadata, download the data (automatically caching it in well organized folders), and all from an interface that looks like a humble dict with owner/dataset keys, and that's the coolest bit. Haggle: /ˈ...
In this landmark recognition challenge, the team had to build models that recognize the correct landmark (if any) in a dataset of complicated test images. This is easier said than done, given landmark recognition contains a much larger number of classes. For example, there were more than 81...
pair also used data augmentation to bolster a training dataset of over 3 million fingerspelled characters, which were captured via smartphone videos and then converted into x, y and z coordinates that corresponded to the position of the signer’s face, hand and pose in each frame of the ...
当时期间Mask R-CNN有两大开源版本,一个是Matter Port的Keras版代码,另一个是Facebook官方的Caffe2版代码(即Detectron)。 据说Detectron的性能优于Matter Port 10个百分点,因此我直接选择了性能更好的Detectron。其实11月初官方又开源了Pytorch版本Mask R-CNN,如果这个早一点开源的话,首选的必定是Pytorch版,因为这样...
3. Digital Recognition（数字识别）中文教程：大数据竞赛平台—Kaggle 入门 英文教程：Interactive Intro to...