@@ -104,21 +104,19 @@ Below are some common methods used with the Roboflow Python package, presented c
104104``` python
105105import roboflow
106106
107- roboflow.login()
107+ # Pass API key or use roboflow.login()
108+ rf = roboflow.Roboflow(api_key = " MY_API_KEY" )
108109
109- rf = roboflow.Roboflow ()
110+ workspace = rf.workspace ()
110111
111- # create a project
112- rf.create_project(
113- project_name = " project name" ,
114- project_type = " project-type" ,
115- license = " project-license" # "private" for private projects
112+ # creating object detection model that will detect flowers
113+ project = workspace.create_project(
114+ project_name = " Flower detector" ,
115+ project_type = " object-detection" , # Or "classification", "instance-segmentation", "semantic-segmentation"
116+ project_license = " MIT" , # "private" for private projects, only available for paid customers
117+ annotation = " flowers" # If you plan to annotate lillys, sunflowers, etc.
116118)
117119
118- workspace = rf.workspace(" WORKSPACE_URL" )
119- project = workspace.project(" PROJECT_URL" )
120- version = project.version(" VERSION_NUMBER" )
121-
122120# upload a dataset
123121workspace.upload_dataset(
124122 dataset_path = " ./dataset/" ,
@@ -128,12 +126,9 @@ workspace.upload_dataset(
128126 project_type = " object-detection"
129127)
130128
131- # upload model weights
132- version.deploy(model_type = " yolov8" , model_path = f”{HOME }/ runs/ detect/ train/ ”)
129+ version = project.version(" VERSION_NUMBER" )
133130
134131# upload model weights - yolov10
135- # Before attempting to upload YOLOv10 models install ultralytics like this:
136- # pip install git+https://github.com/THU-MIG/yolov10.git
137132version.deploy(model_type = " yolov10" , model_path = f”{HOME }/ runs/ detect/ train/ ”, filename = " weights.pt" )
138133
139134# run inference
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