o e"V@sddlZddlZddlZddlZddlZddlZddlZddlZddlZddl Z ddl Z ddl Z ddl mZddlmZmZmZddlmZddlmZddlmZddlmZGdd d eZdS) NImage)API_URLOBJECT_DETECTION_MODELOBJECT_DETECTION_URL)InferenceModel)check_image_url)PredictionGroup)*print_warn_for_wrong_dependencies_versionscseZdZdZ           dfdd Z       dd d Z       dd d Z        d ddZd!ddZd"ddZ        d#ddZ ddZ Z S)$ObjectDetectionModelzm Run inference on an object detection model hosted on Roboflow or served through Roboflow Inference. N(Fjsoncstt|||||_||_||_|p|j|_||_||_||_ | |_ | |_ | |_ | dur0in| |_ | dur9in| |_|durFtd|_n td|||_|dur]|dur_|dSdSdS)a Create a ObjectDetectionModel object through which you can run inference. Args: api_key (str): Your API key (obtained via your workspace API settings page). name (str): The url-safe version of the dataset name. You can find it in the web UI by looking at the URL on the main project view or by clicking the "Get curl command" button in the train results section of your dataset version after training your model. local (str): Address of the local server address if running a local Roboflow deployment server. Ex. http://localhost:9001/ version (str): The version number identifying the version of your dataset. classes (str): Restrict the predictions to only those of certain classes. Provide as a comma-separated string. overlap (int): The maximum percentage (on a scale of 0-100) that bounding box predictions of the same class are allowed to overlap before being combined into a single box. confidence (int): A threshold for the returned predictions on a scale of 0-100. A lower number will return more predictions. A higher number will return fewer high-certainty predictions. stroke (int): The width (in pixels) of the bounding box displayed around predictions (only has an effect when format is image). labels (bool): Whether or not to display text labels on the predictions (only has an effect when format is image). format (str): The format of the output. - 'json': returns an array of JSON predictions (See response format tab). - 'image': returns an image with annotated predictions as a binary blob with a Content-Type of image/jpeg. N/z4initalizing local object detection model hosted at :)superr __init___ObjectDetectionModel__api_keyidnameversionclassesoverlap confidencestrokelabelsformatcolors preprocessingrbase_urlprint#_ObjectDetectionModel__generate_url)selfapi_keyrrrlocalrrrrrrrr __class__O/var/www/myenv/lib/python3.10/site-packages/roboflow/models/object_detection.pyrs(+    zObjectDetectionModel.__init__c Cs(||_||_|j||||||| ddS)a- Loads a Model from on a model endpoint. Args: name (str): The url-safe version of the dataset name version (str): The version number identifying the version of your dataset. local (bool): Whether the model is hosted locally or on Roboflow )r$rrrrrrN)rrr!) r"rrr$rrrrrrr'r'r( load_model`s zObjectDetectionModel.load_modelc Cs|j||||||dt|ddurn|j|dd} |st|trt|d} | j} t | } d|j vrm| dt |j dd ksS| d t |j dd krm| t |j dd t |j dd f} | j} d} t} | j| d d t| }|d}tj|j|ddid}t| dt| d d}nHt|tjrtd|\}}|j} t|}|d}tj|j|ddid}ddd}ntd|jdtj !|7_ddd}t|j}|"|j#dkro|$}| rdg}|dD]c}t |dt | dt |j dd |d<t |dt | d t |j dd |d<t |d t | dt |j dd |d <t |d t | d t |j dd |d <|%|q||d<t&j'||t(||j)dS|j#dkrx|j*SdS)a Infers detections based on image from specified model and image path. Args: image_path (str): path to the image you'd like to perform prediction on hosted (bool): whether the image you're providing is hosted on Roboflow format (str): The format of the output. Returns: PredictionGroup Object Example: >>> import roboflow >>> rf = roboflow.Roboflow(api_key="") >>> project = rf.workspace().project("PROJECT_ID") >>> model = project.version("1").model >>> prediction = model.predict("YOUR_IMAGE.jpg") )rrrrrr__len__T)image_path_checkFRGBresizerwidthrheightPNG)rascii Content-Type!application/x-www-form-urlencodeddataheaders)r.r/z.jpg0z-image_path must be a string or a numpy array.z&image=r predictionsxy) image_pathprediction_type image_dimsrimageN)+r!hasattr&_ObjectDetectionModel__exception_check isinstancestrropenconvertsizecopydeepcopyrkeysintr-ioBytesIOsavebase64 b64encodegetvaluedecoderequestspostapi_urlnpndarraycv2imencodeshape ValueErrorurllibparse quote_plusraise_for_statusrrappendr create_prediction_grouprrcontent)r"r;hostedrrrrrrr-r> dimensionsoriginal_dimensionsbufferedimg_strrespr=retvalbuffer resp_json new_predspr'r'r(predicts"    "            ..$$  zObjectDetectionModel.predictrhttps://detect.roboflow.com/roc sPdtjd<j|||||ddfdd t|dus#s+tdt|tj dtj d rtdtjd<t d gt d gddl } ddl } dd lmdd lm} | ddd| jdddddddn tdtjtdfdd} r| | j| fd} | dS| dS)ae Infers detections based on webcam feed from specified model. Args: webcam_id (int): Webcam ID (default 0) inference_engine_url (str): Inference engine address to use (default https://detect.roboflow.com) within_jupyter (bool): Whether or not to display the webcam within Jupyter notebook (default True) confidence (int): Confidence threshold for detections overlap (int): Overlap threshold for detections stroke (int): Stroke width for bounding box labels (bool): Whether to show labels on bounding box r7OPENCV_VIDEOIO_PRIORITY_MSMF)rrrrinference_engine_urlNc sv|durin|_||vr(|dur(||dtfdddDn ddtdD|pDtd|jd |jd d d }t|d t|d ft|d t|df}}tj ||||tj d |rt |d d } tj |d |d| d d } |d | d |d | d df}t |||dtj tj |||d |d d fd |dgd| tj d dSdS)N#c3s&|]}t||ddVqdS)N)rI).0icolorr'r( >s$zDObjectDetectionModel.webcam..plot_one_box..)rrscSsg|]}tddqS)r)randomrandint)ru_r'r'r( @szEObjectDetectionModel.webcam..plot_one_box..gMb`?rrrs) thicknesslineType) fontScaler)r{r{)rrHlstriptuplerangeroundrXrIrV rectangleLINE_AAmax getTextSizeputText) r9imgrxlabelline_thicknessrtlc1c2tft_size)r"rwr( plot_one_box6s2 (2$ z1ObjectDetectionModel.webcam..plot_one_boxz!No webcam available at webcam_id rr)IPython>=7.0.0) ipywidgetsrrr)displayzloading Roboflow model...T) display_idFzStop Inferencedanger Descriptionsquare)value descriptiondisabled button_styletooltipiconRoboflow Webcam Inferencec s dur jdur nn tdd@tdkrn͈\}}t|}t|d}td|\}}t |}| d}t j j |ddid }|}|d }g}g} |D]c} | d | d | d | d | d g} t| d| dd| d<t| d| dd| d<t| d| dd| d<t| d| dd| d<|| | | d| || ddjdqUtd|\}} rΈ| dntd|tdd@tdkrnqstdttddS)NTrr{qz.jpegr1r2r3r4r8r9r:rrr.rsr/rclass)rrr)r5r)rrVwaitKeyordreadr-fliprWrMrNrPrQrRrSrrIr^rupdatetobytesimshowrelease destroyWindowdestroyAllWindows) buttonr~frame frame_uploadrerrr8formatted_predictionsrpredformatted_pred frame_display IPythonImagecapdisplay_handlerr" stopButton web_cam_reswithin_jupyterr'r(view}sp         C  z)ObjectDetectionModel.webcam..view)targetargs)NNNN)osenvironr!rV VideoCaptureisOpened ExceptionrBsetCAP_PROP_FRAME_WIDTHCAP_PROP_FRAME_HEIGHTr threadingrIPython.displayrr ToggleButton namedWindow WINDOW_NORMALstartWindowThreadThreadstart)r" webcam_idrqrrrrrrrwidgetsrrthreadr'rr(webcamsP  !       L  zObjectDetectionModel.webcampt.cs dg}||vrtd|d||jd\}}}td|d|d|jd}tj|d|jid}|| d} dfd d } tj| d d } t dd4} t | j d} t | jddddt | dddD] }|r}| || qpWddS1swYdS)a Download the weights associated with a model. Args: format (str): The format of the output. - 'pt': returns a PyTorch weights file location (str): The location to save the weights file to rzUnsupported format z. Must be one of rz/ptFiler#)params weightsUrlPcs@ddd||d||f}tjd|tjdS)NDownloading weights to /weights.ptz: %d%% [%d / %d] bytesd )sysstdoutwriteflush)currenttotalr.progress_messagelocationr'r( bar_progresssz3ObjectDetectionModel.download..bar_progressT)streamrwbzcontent-lengthi) chunk_sizerr)descrN)r)rrrsplitrrrQgetrr]rrCrIr6tqdm iter_contentrr)r"rrsupported_formats workspaceprojectr pt_api_urlrpt_weights_urlrresponsef total_lengthchunkr'rr(downloads4          zObjectDetectionModel.downloadcCs8|durtj|st|std|ddSdSdS)NzImage does not exist at !)rpathexistsrr)r"r+r'r'r(__exception_checks z&ObjectDetectionModel.__exception_checkc Cs"|dur|s td|_nd|_|dur||_|dur||_|dur$||_|dur+||_|dur2||_|dur9||_|dur@||_|j d} | d} d |j| dt |j d|j ddt |jd t |jd t |jd t |jd |jg|_|jdur|jd |j7_dSdS)z7 Generate the URL to run inference on. Nrzhttp://localhost:9001/rz ?api_key=z&name=YOUR_IMAGE.jpgz &overlap=z &confidence=z&stroke=z&labels=z&format=z &classes=)rrrrrrrrrrjoinrBrrlowerrS) r"r$rrrrrrrqsplittedwithout_workspacer'r'r(__generate_url sD      z#ObjectDetectionModel.__generate_urlc Cs\|jd}|d}|dt|j|j|j|j|j|j|j|j |j |j d }t j |ddS)Nrr) rrrrrrrrrrrs)indent)rrrBrrrrrrrrrrdumps)r"rr json_valuer'r'r(__str__Cs  zObjectDetectionModel.__str__) NNNNr r rFrNN)NNNNNNN)FNNr r rF)rrmFr r rFrn)rr)N)NNNNNNNN) __name__ __module__ __qualname____doc__rr)rlrrr@r!r  __classcell__r'r'r%r(r sjH %   > 2  :r )rMrFrJrrr|rrZrVnumpyrTrQrPILrroboflow.configrrrroboflow.models.inferencerroboflow.util.image_utilsrroboflow.util.predictionr roboflow.util.versionsr r r'r'r'r(s&