From bf446de2c1c52838d470a83253086046d60ac491 Mon Sep 17 00:00:00 2001 From: weishengyu Date: Mon, 1 Nov 2021 01:31:57 +0800 Subject: [PATCH] update index page --- README_ch.md | 8 +++- README_en.md | 2 +- deploy/configs/build_drinks.yaml | 36 ++++++++++++++++++ deploy/configs/inference_drink.yaml | 55 ++++++++++++++++++++++++++++ docs/images/structure.jpg | Bin 0 -> 101036 bytes docs/images/structure.png | Bin 293757 -> 0 bytes 6 files changed, 99 insertions(+), 2 deletions(-) create mode 100644 deploy/configs/build_drinks.yaml create mode 100644 deploy/configs/inference_drink.yaml create mode 100644 docs/images/structure.jpg delete mode 100644 docs/images/structure.png diff --git a/README_ch.md b/README_ch.md index 007e9b2b..3d7aa2fa 100644 --- a/README_ch.md +++ b/README_ch.md @@ -7,6 +7,8 @@ 飞桨图像识别套件PaddleClas是飞桨为工业界和学术界所准备的一个图像识别任务的工具集,助力使用者训练出更好的视觉模型和应用落地。 **近期更新** +- 2021.10.31 优化文档,新增饮料识别demo +- 2021.10.23 新增轻量级检测、特征提取模型,新增DeepHash模块,检索模块切换为faiss,支持PaddleServing和PaddleSlim - 2021.09.17 增加PaddleClas自研PP-LCNet系列模型, 这些模型在Intel CPU上有较强的竞争力。PP-LCNet的介绍可以参考[论文](https://arxiv.org/pdf/2109.15099.pdf)或者[PP-LCNet模型介绍](docs/zh_CN/models/PP-LCNet.md),相关指标和预训练权重可以从 [这里](docs/zh_CN/ImageNet_models_cn.md)下载。 - 2021.08.11 更新7个[FAQ](docs/zh_CN/faq_series/faq_2021_s2.md)。 - 2021.06.29 添加Swin-transformer系列模型,ImageNet1k数据集上Top1 acc最高精度可达87.2%;支持训练预测评估与whl包部署,预训练模型可以从[这里](docs/zh_CN/models/models_intro.md)下载。 @@ -90,7 +92,7 @@ Res2Net200_vd预训练模型Top-1精度高达85.1%。 ## 图像识别系统介绍
- +
整个图像识别系统分为三步:(1)通过一个目标检测模型,检测图像物体候选区域(2)对每个候选区域进行特征提取(3)与检索库中图像进行特征匹配,提取识别结果。 @@ -110,6 +112,10 @@ Res2Net200_vd预训练模型Top-1精度高达85.1%。 ## 更多效果展示 [more](https://github.com/PaddlePaddle/PaddleClas/tree/release/2.2/docs/images/recognition/more_demo_images) +- 瓶装饮料识别 +
+ +
- 商品识别
diff --git a/README_en.md b/README_en.md index c952621f..4245d5e9 100644 --- a/README_en.md +++ b/README_en.md @@ -84,7 +84,7 @@ Quick experience of image recognition:[Link](./docs/en/tutorials/quick_start_r ## Introduction to Image Recognition Systems
- +
Image recognition can be divided into three steps: diff --git a/deploy/configs/build_drinks.yaml b/deploy/configs/build_drinks.yaml new file mode 100644 index 00000000..79735e1a --- /dev/null +++ b/deploy/configs/build_drinks.yaml @@ -0,0 +1,36 @@ +Global: + rec_inference_model_dir: "./models/general_PPLCNet_x2_5_lite_v1.0_infer" + batch_size: 32 + use_gpu: True + enable_mkldnn: False + cpu_num_threads: 10 + enable_benchmark: False + use_fp16: False + ir_optim: True + use_tensorrt: False + gpu_mem: 8000 + enable_profile: False + +RecPreProcess: + transform_ops: + - ResizeImage: + size: 224 + - NormalizeImage: + scale: 0.00392157 + mean: [0.485, 0.456, 0.406] + std: [0.229, 0.224, 0.225] + order: '' + - ToCHWImage: + +RecPostProcess: null + +# indexing engine config +IndexProcess: + index_method: "HNSW32" # supported: HNSW32, IVF, Flat + index_dir: "./drink_dataset/index" + image_root: "./drink_dataset" + data_file: "./drink_dataset/drink_label.txt" + index_operation: "new" # suported: "append", "remove", "new" + delimiter: " " + dist_type: "IP" + embedding_size: 512 diff --git a/deploy/configs/inference_drink.yaml b/deploy/configs/inference_drink.yaml new file mode 100644 index 00000000..57c0ecb7 --- /dev/null +++ b/deploy/configs/inference_drink.yaml @@ -0,0 +1,55 @@ +Global: + infer_imgs: "./recognition_demo_data_v1.2/test_drinks/hongniu_1.jpg" + det_inference_model_dir: "./models/picodet_PPLCNet_x2_5_mainbody_lite_v1.0_infer" + rec_inference_model_dir: "./models/general_PPLCNet_x2_5_lite_v1.0_infer" + rec_nms_thresold: 0.05 + + batch_size: 1 + image_shape: [3, 640, 640] + threshold: 0.2 + max_det_results: 5 + labe_list: + - foreground + + # inference engine config + use_gpu: True + enable_mkldnn: False + cpu_num_threads: 10 + enable_benchmark: True + use_fp16: False + ir_optim: True + use_tensorrt: False + gpu_mem: 8000 + enable_profile: False + +DetPreProcess: + transform_ops: + - DetResize: + interp: 2 + keep_ratio: false + target_size: [640, 640] + - 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