add batch_name parameter to command line

CLI-COMMANDS.md

@@ -78,6 +78,7 @@ options:
   -w WORKSPACE    specify a workspace url or id (will use default workspace if not specified)
   -p PROJECT      project will be created if it does not exist
   -c CONCURRENCY  how many image uploads to perform concurrently (default: 10)
+  -n BATCH_NAME   name of batch to upload to within project
 ```
 
 ## Example: download dataset

roboflow/adapters/rfapi.py

@@ -5,7 +5,7 @@
 import requests
 from requests_toolbelt.multipart.encoder import MultipartEncoder
 
-from roboflow.config import API_URL, DEFAULT_BATCH_NAME
+from roboflow.config import API_URL, DEFAULT_BATCH_NAME, DEFAULT_JOB_NAME
 from roboflow.util import image_utils
 
 
@@ -58,7 +58,6 @@ def upload_image(
 
     # If image is not a hosted image
     if not hosted_image:
-        batch_name = batch_name or DEFAULT_BATCH_NAME
         image_name = os.path.basename(image_path)
         imgjpeg = image_utils.file2jpeg(image_path)
 
@@ -103,6 +102,7 @@ def save_annotation(
     annotation_name: str,
     annotation_string: str,
     image_id: str,
+    job_name: str = DEFAULT_JOB_NAME,
     is_prediction: bool = False,
     annotation_labelmap=None,
     overwrite: bool = False,
@@ -115,7 +115,9 @@ def save_annotation(
         image_id (str): image id you'd like to upload that has annotations for it.
     """
 
-    upload_url = _save_annotation_url(api_key, project_url, annotation_name, image_id, is_prediction, overwrite)
+    upload_url = _save_annotation_url(
+        api_key, project_url, annotation_name, image_id, job_name, is_prediction, overwrite
+    )
 
     response = requests.post(
         upload_url,
@@ -143,8 +145,10 @@ def save_annotation(
     return responsejson
 
 
-def _save_annotation_url(api_key, project_url, name, image_id, is_prediction, overwrite=False):
+def _save_annotation_url(api_key, project_url, name, image_id, job_name, is_prediction, overwrite=False):
     url = f"{API_URL}/dataset/{project_url}/annotate/{image_id}?api_key={api_key}" f"&name={name}"
+    if job_name:
+        url += f"&jobName={job_name}"
     if is_prediction:
         url += "&prediction=true"
     if overwrite:

roboflow/config.py

@@ -71,6 +71,7 @@ def get_conditional_configuration_variable(key, default):
 TYPE_SEMANTIC_SEGMENTATION = "semantic-segmentation"
 
 DEFAULT_BATCH_NAME = "Pip Package Upload"
+DEFAULT_JOB_NAME = "Annotated via API"
 
 RF_WORKSPACES = get_conditional_configuration_variable("workspaces", default={})
 

roboflow/core/project.py

@@ -9,7 +9,7 @@
 from PIL import Image, UnidentifiedImageError
 
 from roboflow.adapters import rfapi
-from roboflow.config import API_URL, DEFAULT_BATCH_NAME, DEMO_KEYS
+from roboflow.config import API_URL, DEMO_KEYS
 from roboflow.core.version import Version
 from roboflow.util.general import retry
 from roboflow.util.image_utils import load_labelmap
@@ -362,7 +362,7 @@ def upload(
         image_id: str = None,
         split: str = "train",
         num_retry_uploads: int = 0,
-        batch_name: str = DEFAULT_BATCH_NAME,
+        batch_name: str = None,
         tag_names: list = [],
         is_prediction: bool = False,
         **kwargs,
@@ -455,7 +455,7 @@ def single_upload(
         image_id=None,
         split="train",
         num_retry_uploads=0,
-        batch_name=DEFAULT_BATCH_NAME,
+        batch_name=None,
         tag_names=[],
         is_prediction: bool = False,
         annotation_overwrite=False,
@@ -507,6 +507,7 @@ def single_upload(
                     annotation_name,
                     annotation_str,
                     image_id,
+                    job_name=batch_name,
                     is_prediction=is_prediction,
                     annotation_labelmap=annotation_labelmap,
                     overwrite=annotation_overwrite,

roboflow/core/workspace.py

@@ -273,6 +273,7 @@ def upload_dataset(
         num_workers: int = 10,
         project_license: str = "MIT",
         project_type: str = "object-detection",
+        batch_name=None,
     ):
         """
         Upload a dataset to Roboflow.
@@ -344,6 +345,7 @@ def _upload_image(imagedesc):
                     split=split,
                     sequence_number=imagedesc.get("index"),
                     sequence_size=len(images),
+                    batch_name=batch_name,
                 )
                 _log_img_upload(image_path, uploadres)
             except Exception as e:

roboflow/roboflowpy.py

@@ -6,7 +6,7 @@
 import roboflow
 from roboflow import config as roboflow_config
 from roboflow.adapters import rfapi
-from roboflow.config import APP_URL, DEFAULT_BATCH_NAME, get_conditional_configuration_variable, load_roboflow_api_key
+from roboflow.config import APP_URL, get_conditional_configuration_variable, load_roboflow_api_key
 from roboflow.models.classification import ClassificationModel
 from roboflow.models.instance_segmentation import InstanceSegmentationModel
 from roboflow.models.object_detection import ObjectDetectionModel
@@ -48,9 +48,7 @@ def import_dataset(args):
     rf = roboflow.Roboflow()
     workspace = rf.workspace(args.workspace)
     workspace.upload_dataset(
-        dataset_path=args.folder,
-        project_name=args.project,
-        num_workers=args.concurrency,
+        dataset_path=args.folder, project_name=args.project, num_workers=args.concurrency, batch_name=args.batch_name
     )
 
 
@@ -212,7 +210,6 @@ def _add_upload_parser(subparsers):
         "-b",
         dest="batch",
         help="Batch name to upload to (optional)",
-        default=DEFAULT_BATCH_NAME,
     )
     upload_parser.add_argument(
         "-t",
@@ -251,6 +248,11 @@ def _add_import_parser(subparsers):
         help="how many image uploads to perform concurrently (default: 10)",
         default=10,
     )
+    import_parser.add_argument(
+        "-n",
+        dest="batch_name",
+        help="name of batch to upload to within project",
+    )
     import_parser.set_defaults(func=import_dataset)
 
 

tests/manual/debugme.py

@@ -39,6 +39,6 @@
         # f"import {thisdir}/data/cultura-pepino-coco -w wolfodorpythontests -p yellow-auto -c 100".split()  # noqa: E501 // docs
         # f"import {thisdir}/data/cultura-pepino-yolov8 -w wolfodorpythontests -p yellow-auto -c 100".split()  # noqa: E501 // docs
         # f"import {thisdir}/data/cultura-pepino-yolov8_voc -w wolfodorpythontests -p yellow-auto -c 100".split()  # noqa: E501 // docs
-        f"import {thisdir}/data/cultura-pepino-yolov5pytorch -w wolfodorpythontests -p yellow-auto -c 100".split()  # noqa: E501 // docs
+        f"import {thisdir}/data/cultura-pepino-yolov5pytorch -w wolfodorpythontests -p yellow-auto -c 100 -n papaiasso".split()  # noqa: E501 // docs
     )
     args.func(args)