انتقل إلى المحتوى

مرجع ل hub_sdk/base/server_clients.py

ملاحظه

هذا الملف متاح في https://github.com/ultralytics/hub-SDK / نقطة / الرئيسية /hub_sdk / قاعدة / server_clients.py. إذا اكتشفت مشكلة ، فيرجى المساعدة في إصلاحها من خلال المساهمة في طلب 🛠️ سحب. شكرا لك 🙏!



hub_sdk.base.server_clients.ModelUpload

قواعد: APIClient

شفرة المصدر في hub_sdk/base/server_clients.py
class ModelUpload(APIClient):
    def __init__(self, headers):
        """Initialize ModelUpload with API client configuration."""
        super().__init__(f"{HUB_API_ROOT}/v1/models", headers)
        self.name = "model"
        self.alive = True
        self.agent_id = None
        self.rate_limits = {"metrics": 3.0, "ckpt": 900.0, "heartbeat": 300.0}

    def upload_model(self, id, epoch, weights, is_best=False, map=0.0, final=False):
        """
        Upload a model checkpoint to Ultralytics HUB.

        Args:
            epoch (int): The current training epoch.
            weights (str): Path to the model weights file.
            is_best (bool): Indicates if the current model is the best one so far.
            map (float): Mean average precision of the model.
            final (bool): Indicates if the model is the final model after training.
        """
        try:
            # Determine the correct file path
            weights_path = weights if os.path.isabs(weights) else os.path.join(os.getcwd(), weights)

            # Check if the file exists
            if not Path(weights_path).is_file():
                raise FileNotFoundError(f"File not found: {weights_path}")

            with open(weights_path, "rb") as f:
                file = f.read()

            # Prepare the endpoint and data
            endpoint = f"/{id}/upload"
            data = {"epoch": epoch, "type": "final" if final else "epoch"}
            files = {"best.pt": file} if final else {"last.pt": file}
            if final:
                data["map"] = map
            else:
                data["isBest"] = bool(is_best)

            # Perform the POST request
            response = self.post(endpoint, data=data, files=files, stream=True)

            # Log the appropriate message
            msg = "Model optimized weights uploaded." if final else "Model checkpoint weights uploaded."
            self.logger.debug(msg)
            return response
        except Exception as e:
            self.logger.error(f"Failed to upload file for {self.name}: {e}")

    def upload_metrics(self, id: str, data: dict) -> Optional[Response]:
        """
        Upload a file for a specific entity.

        Args:
            id (str): The unique identifier of the entity to which the file is being uploaded.
            data (dict): The metrics data to upload.

        Returns:
            (Optional[Response]): Response object from the upload_metrics request, or None if it fails.
        """
        try:
            payload = {"metrics": data, "type": "metrics"}
            endpoint = f"{HUB_API_ROOT}/v1/models/{id}"
            r = self.post(endpoint, json=payload)
            self.logger.debug("Model metrics uploaded.")
            return r
        except Exception as e:
            self.logger.error(f"Failed to upload metrics for Model({id}): %s", e)

    def export(self, id: str, format: str) -> Optional[Response]:
        """
        Export a file for a specific entity.

        Args:
            id (str): The unique identifier of the entity to which the file is being exported.
            format (str): Path to the file to be Exported.

        Returns:
            (Optional[Response]): Response object from the export request, or None if it fails.
        """
        try:
            payload = {"format": format}
            endpoint = f"/{id}/export"
            return self.post(endpoint, json=payload)
        except Exception as e:
            self.logger.error(f"Failed to export file for Model({id}): %s", e)

    @threaded
    def _start_heartbeats(self, model_id: str, interval: int) -> None:
        """
        Begin a threaded heartbeat loop to report the agent's status to Ultralytics HUB.

        This method initiates a threaded loop that periodically sends heartbeats to the Ultralytics HUB
        to report the status of the agent. Heartbeats are sent at regular intervals as defined in the
        'rate_limits' dictionary.

        Args:
            model_id (str): The unique identifier of the model associated with the agent.
            interval (int): The time interval, in seconds, between consecutive heartbeats.

        Returns:
            (None): The method does not return a value.
        """
        endpoint = f"{HUB_API_ROOT}/v1/agent/heartbeat/models/{model_id}"
        try:
            self.logger.debug(f"Heartbeats started at {interval}s interval.")
            while self.alive:
                payload = {
                    "agent": AGENT_NAME,
                    "agentId": self.agent_id,
                }
                res = self.post(endpoint, json=payload).json()
                new_agent_id = res.get("data", {}).get("agentId")

                self.logger.debug("Heartbeat sent.")

                # Update the agent id as requested by the server
                if new_agent_id != self.agent_id:
                    self.logger.debug("Agent Id updated.")
                    self.agent_id = new_agent_id
                sleep(interval)
        except Exception as e:
            self.logger.error(f"Failed to start heartbeats: {e}")
            raise e

    def _stop_heartbeats(self) -> None:
        """
        Stop the threaded heartbeat loop.

        This method stops the threaded loop responsible for sending heartbeats to the Ultralytics HUB.
        It sets the 'alive' flag to False, which will cause the loop in '_start_heartbeats' to exit.

        Returns:
            (None): The method does not return a value.
        """
        self.alive = False
        self.logger.debug("Heartbeats stopped.")

    def _register_signal_handlers(self) -> None:
        """
        Register signal handlers for SIGTERM and SIGINT signals to gracefully handle termination.

        Returns:
            (None): The method does not return a value.
        """
        signal.signal(signal.SIGTERM, self._handle_signal)  # Polite request to terminate
        signal.signal(signal.SIGINT, self._handle_signal)  # CTRL + C

    def _handle_signal(self, signum: int, frame: Any) -> None:
        """
        Handle kill signals and prevent heartbeats from being sent on Colab after termination.

        This method does not use frame, it is included as it is passed by signal.

        Args:
            signum (int): Signal number.
            frame: The current stack frame (not used in this method).

        Returns:
            (None): The method does not return a value.
        """
        self.logger.debug("Kill signal received!")
        self._stop_heartbeats()
        sys.exit(signum)

    def predict(self, id: str, image: str, config: Dict[str, Any]) -> Optional[Response]:
        """
        Perform a prediction using the specified image and configuration.

        Args:
            id (str): Unique identifier for the prediction request.
            image (str): Image path for prediction.
            config (dict): Configuration parameters for the prediction.

        Returns:
            (Optional[Response]): Response object from the predict request, or None if upload fails.
        """
        try:
            base_path = os.getcwd()
            image_path = os.path.join(base_path, image)

            if not os.path.isfile(image_path):
                raise FileNotFoundError(f"Image file not found: {image_path}")

            with open(image_path, "rb") as f:
                image_file = f.read()

            files = {"image": image_file}
            endpoint = f"{HUB_API_ROOT}/v1/predict/{id}"
            return self.post(endpoint, files=files, data=config)

        except Exception as e:
            self.logger.error(f"Failed to predict for Model({id}): %s", e)

__init__(headers)

تهيئة ModelUpload باستخدام تكوين عميل واجهة برمجة التطبيقات.

شفرة المصدر في hub_sdk/base/server_clients.py
def __init__(self, headers):
    """Initialize ModelUpload with API client configuration."""
    super().__init__(f"{HUB_API_ROOT}/v1/models", headers)
    self.name = "model"
    self.alive = True
    self.agent_id = None
    self.rate_limits = {"metrics": 3.0, "ckpt": 900.0, "heartbeat": 300.0}

export(id, format)

تصدير ملف لكيان معين.

البارامترات:

اسم نوع وصف افتراضي
id str

المعرف الفريد للكيان الذي يتم تصدير الملف إليه.

مطلوب
format str

المسار إلى الملف المراد تصديره.

مطلوب

ارجاع:

نوع وصف
Optional[Response]

كائن الاستجابة من طلب التصدير، أو لا شيء إذا فشل.

شفرة المصدر في hub_sdk/base/server_clients.py
97 98  99 100 101 102 103 104 105 106  107 108109 110111112113
def export(self, id: str, format: str) -> Optional[Response]:
    """
    Export a file for a specific entity.

    Args:
        id (str): The unique identifier of the entity to which the file is being exported.
        format (str): Path to the file to be Exported.

    Returns:
        (Optional[Response]): Response object from the export request, or None if it fails.
    """
    try:
        payload = {"format": format}
        endpoint = f"/{id}/export"
        return self.post(endpoint, json=payload)
    except Exception as e:
        self.logger.error(f"Failed to export file for Model({id}): %s", e)

predict(id, image, config)

قم بإجراء تنبؤ باستخدام الصورة والتكوين المحددين.

البارامترات:

اسم نوع وصف افتراضي
id str

معرف فريد لطلب التنبؤ.

مطلوب
image str

مسار الصورة للتنبؤ.

مطلوب
config dict

معلمات التكوين للتنبؤ.

مطلوب

ارجاع:

نوع وصف
Optional[Response]

كائن الاستجابة من طلب التنبؤ، أو لا شيء إذا فشل التحميل.

شفرة المصدر في hub_sdk/base/server_clients.py
193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218219220
def predict(self, id: str, image: str, config: Dict[str, Any]) -> Optional[Response]:
    """
    Perform a prediction using the specified image and configuration.

    Args:
        id (str): Unique identifier for the prediction request.
        image (str): Image path for prediction.
        config (dict): Configuration parameters for the prediction.

    Returns:
        (Optional[Response]): Response object from the predict request, or None if upload fails.
    """
    try:
        base_path = os.getcwd()
        image_path = os.path.join(base_path, image)

        if not os.path.isfile(image_path):
            raise FileNotFoundError(f"Image file not found: {image_path}")

        with open(image_path, "rb") as f:
            image_file = f.read()

        files = {"image": image_file}
        endpoint = f"{HUB_API_ROOT}/v1/predict/{id}"
        return self.post(endpoint, files=files, data=config)

    except Exception as e:
        self.logger.error(f"Failed to predict for Model({id}): %s", e)

upload_metrics(id, data)

تحميل ملف لكيان معين.

البارامترات:

اسم نوع وصف افتراضي
id str

المعرف الفريد للكيان الذي يتم تحميل الملف إليه.

مطلوب
data dict

بيانات المقاييس المراد تحميلها.

مطلوب

ارجاع:

نوع وصف
Optional[Response]

كائن الاستجابة من طلب upload_metrics أو لا شيء إذا فشل.

شفرة المصدر في hub_sdk/base/server_clients.py
77 78 7980 81 82 83 84 85 86 878889909192939495
def upload_metrics(self, id: str, data: dict) -> Optional[Response]:
    """
    Upload a file for a specific entity.

    Args:
        id (str): The unique identifier of the entity to which the file is being uploaded.
        data (dict): The metrics data to upload.

    Returns:
        (Optional[Response]): Response object from the upload_metrics request, or None if it fails.
    """
    try:
        payload = {"metrics": data, "type": "metrics"}
        endpoint = f"{HUB_API_ROOT}/v1/models/{id}"
        r = self.post(endpoint, json=payload)
        self.logger.debug("Model metrics uploaded.")
        return r
    except Exception as e:
        self.logger.error(f"Failed to upload metrics for Model({id}): %s", e)

upload_model(id, epoch, weights, is_best=False, map=0.0, final=False)

تحميل نقطة تفتيش نموذجية إلى Ultralytics HUB.

البارامترات:

اسم نوع وصف افتراضي
epoch int

حقبة التدريب الحالية.

مطلوب
weights str

المسار إلى ملف أوزان النموذج.

مطلوب
is_best bool

يشير إلى ما إذا كان النموذج الحالي هو الأفضل حتى الآن.

False
map float

متوسط دقة النموذج.

0.0
final bool

يشير إلى ما إذا كان النموذج هو النموذج النهائي بعد التدريب.

False
شفرة المصدر في hub_sdk/base/server_clients.py
36 37 38 39 40 41 42 43 44 45 46 474849 50 51 52 53 54 55 56 57 58 59 60 6162636465 666768697071727374 75
def upload_model(self, id, epoch, weights, is_best=False, map=0.0, final=False):
    """
    Upload a model checkpoint to Ultralytics HUB.

    Args:
        epoch (int): The current training epoch.
        weights (str): Path to the model weights file.
        is_best (bool): Indicates if the current model is the best one so far.
        map (float): Mean average precision of the model.
        final (bool): Indicates if the model is the final model after training.
    """
    try:
        # Determine the correct file path
        weights_path = weights if os.path.isabs(weights) else os.path.join(os.getcwd(), weights)

        # Check if the file exists
        if not Path(weights_path).is_file():
            raise FileNotFoundError(f"File not found: {weights_path}")

        with open(weights_path, "rb") as f:
            file = f.read()

        # Prepare the endpoint and data
        endpoint = f"/{id}/upload"
        data = {"epoch": epoch, "type": "final" if final else "epoch"}
        files = {"best.pt": file} if final else {"last.pt": file}
        if final:
            data["map"] = map
        else:
            data["isBest"] = bool(is_best)

        # Perform the POST request
        response = self.post(endpoint, data=data, files=files, stream=True)

        # Log the appropriate message
        msg = "Model optimized weights uploaded." if final else "Model checkpoint weights uploaded."
        self.logger.debug(msg)
        return response
    except Exception as e:
        self.logger.error(f"Failed to upload file for {self.name}: {e}")



hub_sdk.base.server_clients.ProjectUpload

قواعد: APIClient

شفرة المصدر في hub_sdk/base/server_clients.py
223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246247248249 250251 252 253 254 255256257 258
class ProjectUpload(APIClient):
    def __init__(self, headers: dict):
        """
        Initialize the class with the specified headers.

        Args:
            headers: The headers to use for API requests.
        """
        super().__init__(f"{HUB_API_ROOT}/v1/projects", headers)
        self.name = "project"

    def upload_image(self, id: str, file: str) -> Optional[Response]:
        """
        Upload a project file to the hub.

        Args:
            id (str): The ID of the dataset to upload.
            file (str): The path to the dataset file to upload.

        Returns:
            (Optional[Response]): Response object from the upload image request, or None if it fails.
        """
        base_path = os.getcwd()
        file_path = os.path.join(base_path, file)
        file_name = os.path.basename(file_path)

        with open(file_path, "rb") as image_file:
            project_image = image_file.read()
        try:
            files = {"file": (file_name, project_image)}
            endpoint = f"/{id}/upload"
            r = self.post(endpoint, files=files)
            self.logger.debug("Project Image uploaded successfully.")
            return r
        except Exception as e:
            self.logger.error(f"Failed to upload image for {self.name}({id}): {str(e)}")

__init__(headers)

تهيئة الفئة بالرؤوس المحددة.

البارامترات:

اسم نوع وصف افتراضي
headers dict

الرؤوس المراد استخدامها لطلبات واجهة برمجة التطبيقات.

مطلوب
شفرة المصدر في hub_sdk/base/server_clients.py
224 225 226 227 228229 230 231 232
def __init__(self, headers: dict):
    """
    Initialize the class with the specified headers.

    Args:
        headers: The headers to use for API requests.
    """
    super().__init__(f"{HUB_API_ROOT}/v1/projects", headers)
    self.name = "project"

upload_image(id, file)

قم بتحميل ملف مشروع إلى hub.

البارامترات:

اسم نوع وصف افتراضي
id str

معرف مجموعة البيانات المراد تحميلها.

مطلوب
file str

المسار إلى ملف مجموعة البيانات المراد تحميله.

مطلوب

ارجاع:

نوع وصف
Optional[Response]

كائن الاستجابة من طلب تحميل الصورة، أو لا شيء إذا فشل.

شفرة المصدر في hub_sdk/base/server_clients.py
234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255256257 258
def upload_image(self, id: str, file: str) -> Optional[Response]:
    """
    Upload a project file to the hub.

    Args:
        id (str): The ID of the dataset to upload.
        file (str): The path to the dataset file to upload.

    Returns:
        (Optional[Response]): Response object from the upload image request, or None if it fails.
    """
    base_path = os.getcwd()
    file_path = os.path.join(base_path, file)
    file_name = os.path.basename(file_path)

    with open(file_path, "rb") as image_file:
        project_image = image_file.read()
    try:
        files = {"file": (file_name, project_image)}
        endpoint = f"/{id}/upload"
        r = self.post(endpoint, files=files)
        self.logger.debug("Project Image uploaded successfully.")
        return r
    except Exception as e:
        self.logger.error(f"Failed to upload image for {self.name}({id}): {str(e)}")



hub_sdk.base.server_clients.DatasetUpload

قواعد: APIClient

شفرة المصدر في hub_sdk/base/server_clients.py
261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278279 280 281 282 283 284 285286 287 288289 290 291292293294
class DatasetUpload(APIClient):
    def __init__(self, headers: dict):
        """
        Initialize the class with the specified headers.

        Args:
            headers: The headers to use for API requests.
        """
        super().__init__(f"{HUB_API_ROOT}/v1/datasets", headers)
        self.name = "dataset"

    def upload_dataset(self, id, file) -> Optional[Response]:
        """
        Upload a dataset file to the hub.

        Args:
            id (str): The ID of the dataset to upload.
            file (str): The path to the dataset file to upload.

        Returns:
            (Optional[Response]): Response object from the upload dataset request, or None if it fails.
        """
        try:
            if Path(f"{file}").is_file():
                with open(file, "rb") as f:
                    dataset_file = f.read()
                endpoint = f"/{id}/upload"
                filename = file.split("/")[-1]
                files = {filename: dataset_file}
                r = self.post(endpoint, files=files, stream=True)
                self.logger.debug("Dataset uploaded successfully.")
                return r
        except Exception as e:
            self.logger.error(f"Failed to upload dataset for {self.name}({id}): {str(e)}")

__init__(headers)

تهيئة الفئة بالرؤوس المحددة.

البارامترات:

اسم نوع وصف افتراضي
headers dict

الرؤوس المراد استخدامها لطلبات واجهة برمجة التطبيقات.

مطلوب
شفرة المصدر في hub_sdk/base/server_clients.py
262 263 264 265 266 267 268269 270
def __init__(self, headers: dict):
    """
    Initialize the class with the specified headers.

    Args:
        headers: The headers to use for API requests.
    """
    super().__init__(f"{HUB_API_ROOT}/v1/datasets", headers)
    self.name = "dataset"

upload_dataset(id, file)

قم بتحميل ملف مجموعة بيانات إلى hub.

البارامترات:

اسم نوع وصف افتراضي
id str

معرف مجموعة البيانات المراد تحميلها.

مطلوب
file str

المسار إلى ملف مجموعة البيانات المراد تحميله.

مطلوب

ارجاع:

نوع وصف
Optional[Response]

كائن الاستجابة من طلب مجموعة بيانات التحميل، أو لا شيء إذا فشل.

شفرة المصدر في hub_sdk/base/server_clients.py
272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289290 291292293 294
def upload_dataset(self, id, file) -> Optional[Response]:
    """
    Upload a dataset file to the hub.

    Args:
        id (str): The ID of the dataset to upload.
        file (str): The path to the dataset file to upload.

    Returns:
        (Optional[Response]): Response object from the upload dataset request, or None if it fails.
    """
    try:
        if Path(f"{file}").is_file():
            with open(file, "rb") as f:
                dataset_file = f.read()
            endpoint = f"/{id}/upload"
            filename = file.split("/")[-1]
            files = {filename: dataset_file}
            r = self.post(endpoint, files=files, stream=True)
            self.logger.debug("Dataset uploaded successfully.")
            return r
    except Exception as e:
        self.logger.error(f"Failed to upload dataset for {self.name}({id}): {str(e)}")



hub_sdk.base.server_clients.is_colab()

تحقق مما إذا كانت البيئة الحالية هي Google Colab.

شفرة المصدر في hub_sdk/base/server_clients.py
def is_colab():
    """Check if the current environment is Google Colab."""
    return "google.colab" in platform.sys.modules