Metadata-Version: 2.1
Name: dds-cloudapi-sdk
Version: 0.1.1
Summary: The SDK for calling deepdataspace cloud API.
Home-page: https://github.com/deepdataspace/dds-cloudapi-sdk
Author: cvr@idea
License: UNKNOWN
Description: # dds-cloudapi-sdk
        
        ---
        
        <div align="center">
        <p align="center">
        
        <!-- prettier-ignore -->
        **The Python SDK for the DDS Cloud API.**
        ---
        
        <!-- prettier-ignore -->
        
        [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](LICENSE)
        [![PyPI python](https://img.shields.io/pypi/pyversions/dds-cloudapi-sdk)](https://pypi.org/project/dds-cloudapi-sdk)
        [![PyPI version](https://img.shields.io/pypi/v/dds-cloudapi-sdk)](https://pypi.org/project/dds-cloudapi-sdk)
        ![PyPI - Downloads](https://img.shields.io/pypi/dm/dds-cloudapi-sdk)
        
        </p>
        </div>
        
        ---
        
        The dds-cloudapi-sdk is a Python package designed to simplify interactions with the DDS Cloud API. It features:
        
        - **Straightforward** APIs
        - **Unified** interfaces
        - **Handy** utilities
        
        ## Installation
        
        You can get the SDK library directly from PyPi:
        
        ```shell
        pip install dds-cloudapi-sdk
        ```
        
        ## Quick Start
        
        Below is a straightforward example for the popular IVP algorithm:
        
        ```python
        # 1. Initialize the client with your API token.
        from dds_cloudapi_sdk import Config
        from dds_cloudapi_sdk import Client
        
        token = "Your API Token Here"
        config = Config(token)
        client = Client(config)
        
        # 2. Upload local image to the server and get the URL.
        infer_image_url = "https://dev.deepdataspace.com/static/04_a.ae28c1d6.jpg"
        # infer_image_url = client.upload_file("path/to/infer/image.jpg")  # you can also upload local file for processing
        prompt_image_url = infer_image_url  # use the same image for prompt
        
        # 3. Create a task with proper parameters.
        from dds_cloudapi_sdk.tasks import IVPTask
        from dds_cloudapi_sdk.tasks import RectPrompt
        from dds_cloudapi_sdk.tasks import LabelTypes
        
        task = IVPTask(
            prompt_image_url=prompt_image_url,
            prompts=[RectPrompt(rect=[475.18, 550.20, 548.10, 599.92], is_positive=True)],
            infer_image_url=infer_image_url,
            infer_label_types=[LabelTypes.BBox, LabelTypes.Mask],  # infer both bbox and mask
        )
        
        # 4. Run the task and get the result.
        client.run_task(task)
        
        # 5. Parse the result.
        from dds_cloudapi_sdk.tasks.ivp import TaskResult
        
        result: TaskResult = task.result
        
        mask_url = result.mask_url  # the image url with all masks drawn on
        objects = result.objects  # the list of detected objects
        for idx, obj in enumerate(objects):
            # get the detection score
            print(obj.score)  # 0.42
        
            # get the detection bbox
            print(obj.bbox)  # [635.0, 458.0, 704.0, 508.0]
        
            # get the detection mask, it's of RLE format
            print(obj.mask.counts)  # ]o`f08fa14M3L2O2M2O1O1O1O1N2O1N2O1N2N3M2O3L3M3N2M2N3N1N2O...
        
            # convert the RLE format to RGBA image
            mask_image = task.rle2rgba(obj.mask)
            print(mask_image.size)  # (1600, 1170)
        
            # save the image to file
            mask_image.save(f"data/mask_{idx}.png")
        
        ```
        
        For more details on using the SDK, please refer to the [DDS CloudAPI SDK Reference](https://cloudapi-sdk.deepdataspace.com)
        
        ## 3. Apply for an API Token
        Our API is in private beta. Contact us at [deepdataspace_dm@idea.edu.cn](mailto:deepdataspace_dm@idea.edu.cn) to apply for a free API token.  
        Please include a brief introduction to your research or project and how you plan to use the API in your application.  
        We're dedicated to supporting academic research and education and welcome any questions or suggestions.
        
        ## 4. License
        
        This project is released under
        the [Apache 2.0 License](https://github.com/deepdataspace/dds-cloudapi-sdk/blob/main/LICENSE).
        
        ```text
        Copyright 2023-present, IDEA
        
           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.
        ```
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Description-Content-Type: text/markdown
