add see in the dark module

modules/image/image_processing/seeinthedark/README.md

+# seeinthedark
+
+|模型名称|seeinthedark|
+| :--- | :---: |
+|类别|图像 - 暗光增强|
+|网络|ConvNet|
+|数据集|SID dataset|
+|是否支持Fine-tuning|否|
+|模型大小|120MB|
+|最新更新日期|2021-11-02|
+|数据指标|-|
+
+
+## 一、模型基本信息  
+
+- ### 模型介绍
+
+  - 通过大量暗光条件下短曝光和长曝光组成的图像对，以RAW图像为输入，RGB图像为参照进行训练，该模型实现端到端直接将暗光下的RAW图像处理得到可见的RGB图像。
+
+  - 更多详情参考：[Learning to See in the Dark](http://cchen156.github.io/paper/18CVPR_SID.pdf)
+
+
+
+## 二、安装
+
+- ### 1、环境依赖  
+  - rawpy
+  - pillow
+
+- ### 2、安装
+
+  - ```shell
+    $ hub install seeinthedark
+    ```
+  - 如您安装时遇到问题，可参考：[零基础windows安装](../../../../docs/docs_ch/get_start/windows_quickstart.md)
+ | [零基础Linux安装](../../../../docs/docs_ch/get_start/linux_quickstart.md) | [零基础MacOS安装](../../../../docs/docs_ch/get_start/mac_quickstart.md)
+  - 在windows下安装，由于paddledet package会依赖cython-bbox以及pycocotools, 这两个包需要windows用户提前装好，可参考[cython-bbox安装](https://blog.csdn.net/qq_24739717/article/details/105588729)和[pycocotools安装](https://github.com/PaddlePaddle/PaddleX/blob/release/1.3/docs/install.md#pycocotools安装问题)
+## 三、模型API预测
+
+- ### 1、命令行预测
+
+  - ```shell
+    # Read from a raw(Sony, .ARW) file
+    $ hub run seeinthedark --input_path "/PATH/TO/IMAGE"
+    ```
+  - 通过命令行方式实现暗光增强模型的调用，更多请见 [PaddleHub命令行指令](../../../../docs/docs_ch/tutorial/cmd_usage.rst)
+
+- ### 2、代码示例
+
+  - ```python
+    import paddlehub as hub
+
+    denoiser = hub.Module(name="seeinthedark")
+    input_path = "/PATH/TO/IMAGE"
+    # Read from a raw file
+    denoiser.denoising(input_path, output_path='./denoising_result.png', use_gpu=True)  
+    ```
+
+- ### 3、API
+
+  - ```python
+    def denoising(input_path, output_path='./denoising_result.png', use_gpu=False)
+    ```
+    - 暗光增强API，完成对暗光RAW图像的降噪并处理生成RGB图像。
+
+    - **参数**
+
+      - input\_path (str): 暗光图像文件的路径，Sony的RAW格式; <br/>
+      - output\_path (str): 结果保存的路径, 需要指定输出文件名； <br/>
+      - use\_gpu (bool): 是否使用 GPU；<br/>
+
+
+
+
+## 四、更新历史
+
+* 1.0.0
+
+  初始发布
+
+  - ```shell
+    $ hub install seeinthedark==1.0.0
+    ```

modules/image/image_processing/seeinthedark/module.py

+# Copyright (c) 2021 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 os
+import argparse
+
+import paddle
+import paddlehub as hub
+from paddlehub.module.module import moduleinfo, runnable
+import numpy as np
+import rawpy
+from PIL import Image
+
+
+def pack_raw(raw):
+    # pack Bayer image to 4 channels
+    im = raw.raw_image_visible.astype(np.float32)
+    im = np.maximum(im - 512, 0) / (16383 - 512)  # subtract the black level
+
+    im = np.expand_dims(im, axis=2)
+    img_shape = im.shape
+    H = img_shape[0]
+    W = img_shape[1]
+
+    out = np.concatenate((im[0:H:2, 0:W:2, :], im[0:H:2, 1:W:2, :], im[1:H:2, 1:W:2, :], im[1:H:2, 0:W:2, :]), axis=2)
+    return out
+
+
+@moduleinfo(
+    name="seeinthedark", type="CV/denoising", author="paddlepaddle", author_email="", summary="", version="1.0.0")
+class LearningToSeeInDark:
+    def __init__(self):
+        self.pretrained_model = os.path.join(self.directory, "pd_model/inference_model")
+
+    def denoising(self, input_path, output_path='./denoising_result.png', use_gpu=False):
+        '''
+        Denoise a raw image in the low-light scene.
+
+        input_path: the raw image path
+        output_path: the path to save the results
+        use_gpu: if True, use gpu to perform the computation, otherwise cpu.
+        '''
+        paddle.enable_static()
+        if use_gpu == False:
+            exe = paddle.static.Executor(paddle.CPUPlace())
+        else:
+            exe = paddle.static.Executor(paddle.CUDAPlace(0))
+        [prog, inputs, outputs] = paddle.static.load_inference_model(
+            path_prefix=self.pretrained_model,
+            executor=exe,
+            model_filename="model.pdmodel",
+            params_filename="model.pdiparams")
+        raw = rawpy.imread(input_path)
+        input_full = np.expand_dims(pack_raw(raw), axis=0) * 300
+        px = input_full.shape[1] // 512
+        py = input_full.shape[2] // 512
+        rx, ry = px * 512, py * 512
+        input_full = input_full[:, :rx, :ry, :]
+        output = np.random.randn(rx * 2, ry * 2, 3)
+        input_full = np.minimum(input_full, 1.0)
+        for i in range(px):
+            for j in range(py):
+                input_patch = input_full[:, i * 512:i * 512 + 512, j * 512:j * 512 + 512, :]
+                result = exe.run(prog, feed={inputs[0]: input_patch}, fetch_list=outputs)
+                output[i * 512 * 2:i * 512 * 2 + 512 * 2, j * 512 * 2:j * 512 * 2 + 512 * 2, :] = result[0][0]
+        output = np.minimum(np.maximum(output, 0), 1)
+
+        print('Denoising Over.')
+        try:
+            Image.fromarray(np.uint8(output * 255)).save(os.path.join(output_path))
+            print('Image saved in {}'.format(output_path))
+        except:
+            print('Save image failed. Please check the output_path, should\
+                be image format ext, e.g. png. current output path {}'.format(output_path))
+
+    @runnable
+    def run_cmd(self, argvs: list):
+        """
+        Run as a command.
+        """
+        self.parser = argparse.ArgumentParser(
+            description="Run the {} module.".format(self.name),
+            prog='hub run {}'.format(self.name),
+            usage='%(prog)s',
+            add_help=True)
+
+        self.arg_input_group = self.parser.add_argument_group(title="Input options", description="Input data. Required")
+        self.arg_config_group = self.parser.add_argument_group(
+            title="Config options", description="Run configuration for controlling module behavior, not required.")
+        self.add_module_config_arg()
+        self.add_module_input_arg()
+        self.args = self.parser.parse_args(argvs)
+        self.denoising(input_path=self.args.input_path, output_path=self.args.output_path, use_gpu=self.args.use_gpu)
+
+    def add_module_config_arg(self):
+        """
+        Add the command config options.
+        """
+        self.arg_config_group.add_argument('--use_gpu', action='store_true', help="use GPU or not")
+
+        self.arg_config_group.add_argument(
+            '--output_path', type=str, default='denoising_result.png', help='output path for saving result.')
+
+    def add_module_input_arg(self):
+        """
+        Add the command input options.
+        """
+        self.arg_input_group.add_argument(
+            '--input_path', type=str, help="path to input raw image, should be raw file captured by camera.")

modules/image/image_processing/seeinthedark/requirements.txt

+rawpy
+pillow