o eF\@sddlZddlZddlZddlZddlZddlZddlmZmZddl m Z ddl m Z m Z mZddlmZddlmZddlmZdd gZd d Zee_Gd d d ZdS)N)ImageUnidentifiedImageError)rfapi)API_URLDEFAULT_BATCH_NAME DEMO_KEYS)Version)retry) load_labelmapPNGJPEGcOs t|dS)N )str)msgargskwargsrD/var/www/myenv/lib/python3.10/site-packages/roboflow/core/project.pycustom_formatwarnings rc@seZdZdZdEdededefddZdd Zd d Zd d ZddZ ddddddiddddfde fddZ dEde defddZ defdd Zddddd!d"egdf ded#ed$e d%ed&ed'e d(ed)ed*e fd+d,Zdddddd!d"egdf d*e fd-d.Zd/d0Zddd"d1dddddgd2f d3ed4ed5e d6e d7ed8ed9ed:e d;edZddd"d1dddddd?d@gf d3ed4ed5e d6e d7ed8ed9ed:e d;ed>> import roboflow >>> rf = roboflow.Roboflow(api_key="") >>> project = rf.workspace().project("PROJECT_ID") annotationclassescolorscreatedidimagesnamepublicsplitstype unannotatedupdated/rN)r_Project__api_keyrrrrdatetime fromtimestamprrrrr r!r"r#r$rsplit_Project__workspace_Project__project_name)selfrrrtemprrr__init__ s(             zProject.__init__cCsLttd|jd|jd|j}|jdkrt|j| }|dS)ab Retrieve all versions of a project. Returns: A list of all versions of the project. Example: >>> import roboflow >>> rf = roboflow.Roboflow(api_key="") >>> project = rf.workspace().project("PROJECT_ID") >>> version_info = project.get_version_information() r%z ?api_key=versions) requestsgetrr+r,r' status_code RuntimeErrortextjson)r- dataset_inforrrget_version_informationGs   zProject.get_version_informationcCs|}t|dS)a Print out versions for that specific project. Example: >>> import roboflow >>> rf = roboflow.Roboflow(api_key="") >>> project = rf.workspace().project("PROJECT_ID") >>> project.list_versions() N)r9print)r- version_inforrr list_versionsbs zProject.list_versionscCsb|}g}|D]&}t|d|vr|jnd|j|j|d|jd|j|j|j|j d }| |q|S)aV Return all versions in the project as Version objects. Returns: A list of Version objects. Example: >>> import roboflow >>> rf = roboflow.Roboflow(api_key="") >>> project = rf.workspace().project("PROJECT_ID") >>> versions = project.versions() modelNrlocal workspaceprojectr r) r9rr"r'rrr+r,r rappend)r-r; version_array a_versionversion_objectrrrr1rs$ zProject.versionscCsddh|ks tdtjtd|jd|jd|j|d}z|}Wn t y0dw|j dkr[t j d |d d t|d d t j dt j t|d Sd|vrgt|dtt|)a Generate a version of a dataset hosted on Roboflow. Args: settings: A Python dict with augmentation and preprocessing keys and specifications for generation. These settings mirror capabilities available via the Roboflow UI. For example: { "augmentation": { "bbblur": { "pixels": 1.5 }, "bbbrightness": { "brighten": true, "darken": false, "percent": 91 }, "bbcrop": { "min": 12, "max": 71 }, "bbexposure": { "percent": 30 }, "bbflip": { "horizontal": true, "vertical": false }, "bbnoise": { "percent": 50 }, "bbninety": { "clockwise": true, "counter-clockwise": false, "upside-down": false }, "bbrotate": { "degrees": 45 }, "bbshear": { "horizontal": 45, "vertical": 45 }, "blur": { "pixels": 1.5 }, "brightness": { "brighten": true, "darken": false, "percent": 91 }, "crop": { "min": 12, "max": 71 }, "cutout": { "count": 26, "percent": 71 }, "exposure": { "percent": 30 }, "flip": { "horizontal": true, "vertical": false }, "hue": { "degrees": 180 }, "image": { "versions": 32 }, "mosaic": true, "ninety": { "clockwise": true, "counter-clockwise": false, "upside-down": false }, "noise": { "percent": 50 }, "rgrayscale": { "percent": 50 }, "rotate": { "degrees": 45 }, "saturation": { "percent": 50 }, "shear": { "horizontal": 45, "vertical": 45 } }, "preprocessing": { "auto-orient": true, "contrast": { "type": "Contrast Stretching" }, "filter-null": { "percent": 50 }, "grayscale": true, "isolate": true, "remap": { "original_class_name": "new_class_name" }, "resize": { "width": 200, "height": 200, "format": "Stretch to" }, "static-crop": { "x_min": 10, "x_max": 90, "y_min": 10, "y_max": 90 }, "tile": { "rows": 2, "columns": 2 } } } Returns: int: The version number that is being generated. Example: >>> import roboflow >>> rf = roboflow.Roboflow(api_key="") >>> project = rf.workspace().project("PROJECT_ID") >>> versions = project.generate_version(settings={...}) augmentation preprocessingz~augmentation and preprocessing keys are required to generate. If none are desired specify empty dict associated with that key.r%z/generate?api_key=r7z>> import roboflow >>> rf = roboflow.Roboflow(api_key="") >>> project = rf.workspace().project("PROJECT_ID") >>> version = project.version(1) >>> version.train() )rW)speed checkpointplot_in_notebook)rZrKtrain)r-new_version_settingsr`rarb new_version new_modelrrrrcs ( z Project.trainversion_numberr?cCs|jtvr d}|jdkrd}nd}tid|j|||jdddd S|}|D]+}tj|d}|t|krQt||j |j|j ||j||j |j |j |jd }|Sq&td |) aZ Retrieves information about a specific version and returns a Version() object. Args: version_number (int): the version number that you want to retrieve local (str): specifies the localhost address and port if pointing towards local inference engine Returns: Version() object zcoco-128-samplezcoco-128zchess-pieces-newr"N)r?r@rArr>zVersion number {} is not found.)r'rrrr9ospathbasenamerr"rr+r,r rr5r])r-rgr?rr;rEcurrent_version_numversrrrrKsH     zProject.version image_pathcCs8zt|}|jtv}|W|StyYdSw)z Check if an image is valid. Useful before attempting to upload an image to Roboflow. Args: image_path (str): path to image you'd like to check Returns: bool: whether the image is valid or not F)ropenr]ACCEPTED_IMAGE_FORMATScloser)r-rnimgvalidrrrcheck_valid_imageQs    zProject.check_valid_imagercrannotation_path hosted_imageimage_idsplitnum_retry_uploads batch_name tag_names is_predictionc  Ks|dp |d} tj|p| } tj|} | s#| s#td|| rM| p+||}|s9td|dt |j d ||||||||| d | d St |}|D]0}|d|}||r||j d ||||||||| d | t d|d qTt d|d qTd S) a Upload an image or annotation to the Roboflow API. Args: image_path (str): path to image you'd like to upload annotation_path (str): if you're upload annotation, path to it hosted_image (bool): whether the image is hosted image_id (str): id of the image split (str): to upload the image to num_retry_uploads (int): how many times to retry upload on failure batch_name (str): name of batch to upload to within project tag_names (list[str]): tags to be applied to an image is_prediction (bool): whether the annotation data is a prediction rather than ground truth Example: >>> import roboflow >>> rf = roboflow.Roboflow(api_key="") >>> project = rf.workspace().project("PROJECT_ID") >>> project.upload(image_path="YOUR_IMAGE.jpg") zhttp://zhttps://zeThe provided image path [ {} ] is not a valid path. Please provide a path to an image or a directory.zSThe image you provided {} is not a supported file format. We currently support: {}.z, ) rnrurvrwrxryrzr{r|r%z[ z ] was uploaded succesfully.z ] was skipped.Nr) startswithrirjisfileisdirr5r]rtjoinrp single_uploadlistdirr:)r-rnrurvrwrxryrzr{r|r is_hostedis_fileis_diris_imagerimagerjrrruploaddsb%      zProject.uploadc  Ks|jdd} |r|rtd|s|stdt|tr!t|}d\} }|r?t|ttj|j | |f|||| d| } | d}|rn| |\}}ztj |j | |||| |d}Wnt ym}z d |i}WYd}~nd}~ww| |d S) Nr%r&z+You can't pass both image_id and image_pathz'You need to pass image_path or image_idNN)rvrxrzr{r)r|annotation_labelmaprM)rr) rr*rP isinstancerr r r upload_imager'_annotation_paramssave_annotation BaseException)r-rnrurrvrwrxryrzr{r|r project_urluploaded_imageuploaded_annotationannotation_nameannotation_strerrrrsT      zProject.single_uploadcCsd\}}tj|r0t|dt|d}Wdn1s!wYtj|}||fS|jdkrEtd|d|}|}||fStd|)NrrXclassificationz -> using z( as classname for classification projectzVFile not found or uploading to non-classification type project with invalid string. - ) rirjexistsroreadrkr"r:rP)r-rurannotation_stringrrrrs"    zProject._annotation_paramsd)rrrlabels like_imagepromptoffsetlimittag class_name in_datasetbatchbatch_idfieldsc Csi} |dur || d<|dur|| d<|dur|| d<|dur"|| d<|dur*|| d<|dur2|| d<|dur:|| d<|durB|| d <| durJ| | d <| | d <tjtd |jd |jd |j| d} | dS)a Search for images in a project. Args: like_image (str): name of an image in your dataset to use if you want to find images similar to that one prompt (str): search prompt offset (int): offset of results limit (int): limit of results tag (str): tag that an image must have class_name (str): class name that an image must have in_dataset (str): dataset that an image must be in batch (bool): whether the image must be in a batch batch_id (str): batch id that an image must be in fields (list): fields to return in results (default: ["id", "created", "name", "labels"]) Returns: A list of images that match the search criteria. Example: >>> import roboflow >>> rf = roboflow.Roboflow(api_key="") >>> project = rf.workspace().project("PROJECT_ID") >>> results = project.search(query="cat", limit=10) Nrrrrrrrrrrr%z/search?api_key=rHresults)r2rOrr+r,r'r7) r-rrrrrrrrrrpayloaddatarrrsearchs2(  zProject.searchrrc csB |j||||||||| | d } | Vt| |krdS||7}q)a Create a paginated list of search results for use in searching the images in a project. Args: like_image (str): name of an image in your dataset to use if you want to find images similar to that one prompt (str): search prompt offset (int): offset of results limit (int): limit of results tag (str): tag that an image must have class_name (str): class name that an image must have in_dataset (str): dataset that an image must be in batch (bool): whether the image must be in a batch batch_id (str): batch id that an image must be in fields (list): fields to return in results (default: ["id", "created", "name", "labels"]) Returns: A list of images that match the search criteria. Example: >>> import roboflow >>> rf = roboflow.Roboflow(api_key="") >>> project = rf.workspace().project("PROJECT_ID") >>> results = project.search_all(query="cat", limit=10) >>> for result in results: >>> print(result) T) rrrrrrrrrrN)rlen) r-rrrrrrrrrrrrrr search_allUs&, zProject.search_allcCs |j|j|jd}tj|ddS)zC Show a string representation of a Project object. )rr"r@)indent)rr"r+r7rV)r-json_strrrr__str__szProject.__str__)N)__name__ __module__ __qualname____doc__rr/r9r<r1rZboolrcrUrKrtrlistrrrrrrrrrrrs'#^  .4  ^ 6   P   Ar)r(r7rirQwarningsr2PILrrroboflow.adaptersrroboflow.configrrrroboflow.core.versionrroboflow.util.generalr roboflow.util.image_utilsr rpr formatwarningrrrrrs