## Detailed Features ### 1\. Various Pre-training Models #### 1.1. Image | | **Examples of Boutique Models** | | -------------------- | :----------------------------------------------------------- | | Image Classification | [Dish Identification](https://www.paddlepaddle.org.cn/hubdetail?name=resnet50_vd_dishes&en_category=ImageClassification), [Animal Identification](https://www.paddlepaddle.org.cn/hubdetail?name=resnet50_vd_animals&en_category=ImageClassification), [Animal Identification](https://www.paddlepaddle.org.cn/hubdetail?name=resnet50_vd_animals&en_category=ImageClassification), [-->More](../modules/image/classification/README.md) | | Object Detection | [Universal Detection](https://www.paddlepaddle.org.cn/hubdetail?name=yolov3_darknet53_coco2017&en_category=ObjectDetection), [Pedestrian Detection](https://www.paddlepaddle.org.cn/hubdetail?name=yolov3_darknet53_pedestrian&en_category=ObjectDetection), [Vehicle Detection](https://www.paddlepaddle.org.cn/hubdetail?name=yolov3_darknet53_vehicles&en_category=ObjectDetection), [-->More](../modules/image/object_detection/README.md) | | Face Detection | [Face Detection](https://www.paddlepaddle.org.cn/hubdetail?name=pyramidbox_lite_server&en_category=FaceDetection), [Mask Detection](https://www.paddlepaddle.org.cn/hubdetail?name=pyramidbox_lite_server_mask&en_category=FaceDetection), [-->More](../modules/image/face_detection/README.md) | | Image Segmentation | [Portrait Segmentation](https://www.paddlepaddle.org.cn/hubdetail?name=deeplabv3p_xception65_humanseg&en_category=ImageSegmentation), [Body Analysis](https://www.paddlepaddle.org.cn/hubdetail?name=ace2p&en_category=ImageSegmentation), [Pneumonia CT Imaging Analysis](https://www.paddlepaddle.org.cn/hubdetail?name=Pneumonia_CT_LKM_PP&en_category=ImageSegmentation), [-->More](../modules/image/semantic_segmentation/README.md) | | Key Point Detection | [Body Key Points](https://www.paddlepaddle.org.cn/hubdetail?name=human_pose_estimation_resnet50_mpii&en_category=KeyPointDetection), [Face Key Points](https://www.paddlepaddle.org.cn/hubdetail?name=face_landmark_localization&en_category=KeyPointDetection), [Hands Key Points](https://www.paddlepaddle.org.cn/hubdetail?name=hand_pose_localization&en_category=KeyPointDetection), [-->More](./modules/image/keypoint_detection/README.md) | | Text Recognition | [Ultra Lightweight Chinese \& English OCR Text Recognition](https://www.paddlepaddle.org.cn/hubdetail?name=chinese_ocr_db_crnn_mobile&en_category=TextRecognition), [-->More](../modules/image/text_recognition/README.md) | | Image Generation | [Style Migration](https://www.paddlepaddle.org.cn/hubdetail?name=stylepro_artistic&en_category=GANs), [Street View Cartoon](https://www.paddlepaddle.org.cn/hubdetail?name=animegan_v2_hayao_99&en_category=GANs), [-->More](../modules/image/Image_gan/README.md) | | Image Editing | [Super Resolution](https://www.paddlepaddle.org.cn/hubdetail?name=realsr&en_category=ImageEditing), [B\&W Color](https://www.paddlepaddle.org.cn/hubdetail?name=deoldify&en_category=ImageEditing), [-->More](../modules/image/Image_editing/README.md) | #### 1.2 Text | | **Examples of Boutique Models** | | ------------------ | :----------------------------------------------------------- | | Word Analysis | [Linguistic Analysis](https://www.paddlepaddle.org.cn/hubdetail?name=lac&en_category=LexicalAnalysis), [Syntactic Analysis](https://www.paddlepaddle.org.cn/hubdetail?name=ddparser&en_category=SyntacticAnalysis), [-->More](../modules/text/lexical_analysis/README.md) | | Sentiment Analysis | [Emotion Judgment](https://www.paddlepaddle.org.cn/hubdetail?name=lac&en_category=LexicalAnalysis), [Emotion Analysis](https://www.paddlepaddle.org.cn/hubdetail?name=emotion_detection_textcnn&en_category=SentimentAnalysis), [-->More](../modules/text/sentiment_analysis/README.md) | | Text Review | [Porn Review](https://www.paddlepaddle.org.cn/hubdetail?name=porn_detection_gru&en_category=TextCensorship), [-->More](../modules/text/text_review/README.md) | | Text Generation | [Poetic Couplet Generation](https://www.paddlepaddle.org.cn/hubdetail?name=ernie_tiny_couplet&en_category=TextGeneration), [Love Letters Generation](https://www.paddlepaddle.org.cn/hubdetail?name=ernie_gen_poetry&en_category=TextGeneration), [Popular Love Letters](https://www.paddlepaddle.org.cn/hubdetail?name=ernie_gen_lover_words&en_category=TextGeneration), [-->More](../modules/text/text_generation/README.md) | | Semantic Models | [ERNIE](https://www.paddlepaddle.org.cn/hubdetail?name=ERNIE&en_category=SemanticModel), [Text Similarity](https://www.paddlepaddle.org.cn/hubdetail?name=simnet_bow&en_category=SemanticModel), [-->More](../modules/text/language_model/README.md) | #### 1.3. Speech | | **Examples of Boutique Models** | | -------------- | :-------------------------------------------------------- | | Text-to-speech | [Text-to-speech](https://www.paddlepaddle.org.cn/hubdetail?name=deepvoice3_ljspeech&en_category=TextToSpeech), [-->More](../modules/audio/README.md) | #### 1.4. Video | | **Examples of Boutique Models** | | -------------------- | :----------------------------------------------------------- | | Video Classification | [ Video Classification](https://www.paddlepaddle.org.cn/hublist?filter=en_category&value=VideoClassification), [-->More](../modules/video/README.md) | ### 2\. One-key Model Prediction * For example, if you use the lightweight Chinese OCR model chinese\_ocr\_db\_crnn\_mobile for text recognition, you can quickly recognize the text in an image with pressing one key. ```shell $ pip install paddlehub $ wget https://paddlehub.bj.bcebos.com/model/image/ocr/test_ocr.jpg $ hub run chinese_ocr_db_crnn_mobile --input_path test_ocr.jpg --visualization=True ``` * The prediction results images are stored in the ocr\_result folder under the current path, as shown in the following figure.
* Use the lexical analysis model LAC for word segmentation. ```shell $ hub run lac --input_text "现在,慕尼黑再保险公司不仅是此类行动的倡议者,更是将其大量气候数据整合进保险产品中,并与公众共享大量天气信息,参与到新能源领域的保障中。" [{ 'word': ['现在', ',', '慕尼黑再保险公司', '不仅', '是', '此类', '行动', '的', '倡议者', ',', '更是', '将', '其', '大量', '气候', '数据', '整合', '进', '保险', '产品', '中', ',', '并', '与', '公众', '共享', '大量', '天气', '信息', ',', '参与', '到', '新能源', '领域', '的', '保障', '中', '。'], 'tag': ['TIME', 'w', 'ORG', 'c', 'v', 'r', 'n', 'u', 'n', 'w', 'd', 'p', 'r', 'a', 'n', 'n', 'v', 'v', 'n', 'n', 'f', 'w', 'c', 'p', 'n', 'v', 'a', 'n', 'n', 'w', 'v', 'v', 'n', 'n', 'u', 'vn', 'f', 'w'] }] ``` In addition to one-line code prediction, PaddleHub also supports the use of API to revoke the model. For details, refer to the detailed documentation of each model. ### 3\. One-Key to deploy Models as Services PaddleHub provides convenient model-to-service capability to deploy HTTP services for models with one simple command. The LAC lexical analysis service can quickly start with the following commands: ```shell $ hub serving start -m chinese_ocr_db_crnn_mobile ``` For more instructions on using Model Serving, See PaddleHub Model One-Key Model Serving Deployment. ### 4\. Transfer Learning within Ten Lines of Codes With the Fine-tune API, deep learning models can be migrated and learned in computer vision scenarios with a small number of codes. * The [Demo Examples](../demo) provides rich codes for using Fine-tune API, including [Image Classification](../demo/image_classification), [Image Coloring](../demo/colorization), [Style Migration](../demo/style_transfer), and other scenario model migration examples.
Transfer Learning within Ten Lines of Codes
* For a quick online experience, click [PaddleHub Tutorial Collection](https://aistudio.baidu.com/aistudio/projectdetail/231146) to use the GPU computing power provided by AI Studio platform for a quick attempt.