Add PaddleClas infer.py (#107)

* Update README.md * Update README.md * Update README.md * Create README.md * Update README.md * Update README.md * Update README.md * Update README.md * Add evaluation calculate time and fix some bugs * Update classification __init__ * Move to ppseg * Add segmentation doc * Add PaddleClas infer.py * Update PaddleClas infer.py * Delete .infer.py.swp Co-authored-by: Jason <jiangjiajun@baidu.com>
2025-10-21 15:49:31 +08:00 · 2022-08-12 19:50:27 +08:00
parent 0e73c8951b
commit bd7caa17b8
7 changed files with 404 additions and 4 deletions
--- a/examples/vision/segmentation/paddleseg/python/README.md
+++ b/examples/vision/segmentation/paddleseg/python/README.md
@@ -0,0 +1,75 @@
+# PaddleClas模型 Python部署示例
+
+在部署前，需确认以下两个步骤
+
+- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../docs/quick_start/requirements.md)  
+- 2. FastDeploy Python whl包安装，参考[FastDeploy Python安装](../../../../../docs/quick_start/install.md)
+
+本目录下提供`infer.py`快速完成ResNet50_vd在CPU/GPU，以及GPU上通过TensorRT加速部署的示例。执行如下脚本即可完成
+
+```
+# 下载ResNet50_vd模型文件和测试图片
+wget https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz
+tar -xvf ResNet50_vd_infer.tgz
+wget https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
+
+
+#下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd examples/vision/classification/paddleclas/python
+
+# CPU推理
+python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device cpu
+# GPU推理
+python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device gpu
+# GPU上使用TensorRT推理 （注意：TensorRT推理第一次运行，有序列化模型的操作，有一定耗时，需要耐心等待）
+python infer.py --model ResNet50_vd_infer --image ILSVRC2012_val_00000010.jpeg --device gpu --use_trt True
+```
+
+运行完成后返回结果如下所示
+```
+ClassifyResult(
+label_ids: 153,
+scores: 0.686229,
+)
+```
+
+## PaddleClasModel Python接口
+
+```
+fd.vision.classification.PaddleClasModel(model_file, params_file, config_file, runtime_option=None, model_format=Frontend.PADDLE)
+```
+
+PaddleClas模型加载和初始化，其中model_file, params_file为训练模型导出的Paddle inference文件，具体请参考其文档说明[模型导出](https://github.com/PaddlePaddle/PaddleClas/blob/release/2.4/docs/zh_CN/inference_deployment/export_model.md#2-%E5%88%86%E7%B1%BB%E6%A8%A1%E5%9E%8B%E5%AF%BC%E5%87%BA)
+
+**参数**
+
+> * **model_file**(str): 模型文件路径
+> * **params_file**(str): 参数文件路径
+> * **config_file**(str): 推理部署配置文件
+> * **runtime_option**(RuntimeOption): 后端推理配置，默认为None，即采用默认配置
+> * **model_format**(Frontend): 模型格式，默认为Paddle格式
+
+### predict函数
+
+> ```
+> PaddleClasModel.predict(input_image, topk=1)
+> ```
+>
+> 模型预测结口，输入图像直接输出检测结果。
+>
+> **参数**
+>
+> > * **input_image**(np.ndarray): 输入数据，注意需为HWC，BGR格式
+> > * **topk**(int):返回预测概率最高的topk个分类结果
+
+> **返回**
+>
+> > 返回`fastdeploy.vision.ClassifyResult`结构体，结构体说明参考文档[视觉模型预测结果](../../../../../docs/api/vision_results/)
+
+
+## 其它文档
+
+- [PaddleClas 模型介绍](..)
+- [PaddleClas C++部署](../cpp)
+- [模型预测结果说明](../../../../../docs/api/vision_results/)
--- a/examples/vision/segmentation/paddleseg/python/infer.py
+++ b/examples/vision/segmentation/paddleseg/python/infer.py
@@ -0,0 +1,56 @@
+import fastdeploy as fd
+import cv2
+import os
+
+
+def parse_arguments():
+    import argparse
+    import ast
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model", required=True, help="Path of PaddleClas model.")
+    parser.add_argument(
+        "--image", type=str, required=True, help="Path of test image file.")
+    parser.add_argument(
+        "--topk", type=int, default=1, help="Return topk results.")
+    parser.add_argument(
+        "--device",
+        type=str,
+        default='cpu',
+        help="Type of inference device, support 'cpu' or 'gpu'.")
+    parser.add_argument(
+        "--use_trt",
+        type=ast.literal_eval,
+        default=False,
+        help="Wether to use tensorrt.")
+    return parser.parse_args()
+
+
+def build_option(args):
+    option = fd.RuntimeOption()
+
+    if args.device.lower() == "gpu":
+        option.use_gpu()
+
+    if args.use_trt:
+        option.use_trt_backend()
+        option.set_trt_input_shape("inputs", [1, 3, 224, 224],
+                                   [1, 3, 224, 224], [1, 3, 224, 224])
+    return option
+
+
+args = parse_arguments()
+
+# 配置runtime，加载模型
+runtime_option = build_option(args)
+model_file = os.path.join(args.model, "inference.pdmodel")
+params_file = os.path.join(args.model, "inference.pdiparams")
+config_file = os.path.join(args.model, "inference_cls.yaml")
+#model = fd.vision.classification.PaddleClasModel(model_file, params_file, config_file, runtime_option=runtime_option)
+model = fd.vision.classification.ResNet50vd(
+    model_file, params_file, config_file, runtime_option=runtime_option)
+
+# 预测图片分类结果
+im = cv2.imread(args.image)
+result = model.predict(im, args.topk)
+print(result)