[Add Model]Add RKPicodet (#495)

* 11-02/14:35
* 新增输入数据format错误判断
* 优化推理过程，减少内存分配次数
* 支持多输入rknn模型
* rknn模型输出shape为三维时，输出将被强制对齐为4纬。现在将直接抹除rknn补充的shape，方便部分对输出shape进行判断的模型进行正确的后处理。

* 11-03/17:25
* 支持导出多输入RKNN模型
* 更新各种文档
* ppseg改用Fastdeploy中的模型进行转换

* 11-03/17:25
* 新增开源头

* 11-03/21:48
* 删除无用debug代码，补充注释

* 11-04/01:00
* 新增rkpicodet代码

* 11-04/13:13
* 提交编译缺少的文件

* 11-04/14:03
* 更新安装文档

* 11-04/14:21
* 更新picodet_s配置文件

* 11-04/14:21
* 更新picodet自适应输出结果

* 11-04/14:21
* 更新文档

* * 更新配置文件

* * 修正配置文件

* * 添加缺失的python文件

* * 修正文档

* * 修正代码格式问题0

* * 按照要求修改

* * 按照要求修改

* * 按照要求修改

* * 按照要求修改

* * 按照要求修改

* test

examples/vision/detection/paddledetection/rknpu2/python/README.md

@@ -0,0 +1,35 @@
+# PaddleDetection 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/cn/build_and_install/rknpu2.md)
+
+本目录下提供`infer.py`快速完成Picodet在RKNPU上部署的示例。执行如下脚本即可完成
+
+```bash
+# 下载部署示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd FastDeploy/examples/vision/detection/paddledetection/rknpu2/python
+
+# 下载图片
+wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
+
+# copy model
+cp -r ./picodet_s_416_coco_npu /path/to/FastDeploy/examples/vision/detection/rknpu2detection/paddledetection/python
+
+# 推理
+python3 infer.py --model_file ./picodet_s_416_coco_npu/picodet_s_416_coco_npu_3588.rknn  \
+                  --config_file ./picodet_s_416_coco_npu/infer_cfg.yml \
+                  --image 000000014439.jpg
+```
+
+
+## 注意事项
+RKNPU上对模型的输入要求是使用NHWC格式，且图片归一化操作会在转RKNN模型时，内嵌到模型中，因此我们在使用FastDeploy部署时，
+需要先调用DisableNormalizePermute(C++)或`disable_normalize_permute(Python)，在预处理阶段禁用归一化以及数据格式的转换。
+## 其它文档
+
+- [PaddleDetection 模型介绍](..)
+- [PaddleDetection C++部署](../cpp)
+- [模型预测结果说明](../../../../../../docs/api/vision_results/)
+- [转换PaddleDetection RKNN模型文档](../README.md)

examples/vision/detection/paddledetection/rknpu2/python/infer.py

@@ -0,0 +1,59 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import fastdeploy as fd
+import cv2
+import os
+
+
+def parse_arguments():
+    import argparse
+    import ast
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model_file", required=True, help="Path of rknn model.")
+    parser.add_argument("--config_file", required=True, help="Path of config.")
+    parser.add_argument(
+        "--image", type=str, required=True, help="Path of test image file.")
+    return parser.parse_args()
+
+
+def build_option(args):
+    option = fd.RuntimeOption()
+    option.use_rknpu2()
+    return option
+
+
+args = parse_arguments()
+
+# 配置runtime，加载模型
+runtime_option = build_option(args)
+model_file = args.model_file
+params_file = ""
+config_file = args.config_file
+model = fd.vision.detection.RKPicoDet(
+    model_file,
+    params_file,
+    config_file,
+    runtime_option=runtime_option,
+    model_format=fd.ModelFormat.RKNN)
+
+# 预测图片分割结果
+im = cv2.imread(args.image)
+result = model.predict(im.copy())
+print(result)
+
+# 可视化结果
+vis_im = fd.vision.vis_detection(im, result, score_threshold=0.5)
+cv2.imwrite("visualized_result.jpg", vis_im)
+print("Visualized result save in ./visualized_result.jpg")