from diffgram import Project
# TODO replace `Project()` with full credential object - to get started quickly can copy and paste from Share/Developer Auth
project = Project()
# Gets target joint directory
# TODO replace string `joint_dir` with desired name
# This is the dir that will house the combination of next two dirs
join_dir = project.directory.get("joint_dir")
# TODO replace string `first` with desired name
first_dir = project.directory.get("first") # Gets directory object
file_list = first_dir.list_files() # Gets list of files. can add search_term
print("Length", len(file_list))
result = join_dir.add(file_list)
print(result)
# TODO replace string `second` with desired name
second_dir = project.directory.get("second")
file_list = second_dir.list_files()
print("Length", len(file_list))
result = join_dir.add(file_list)
print(result)
# Can add further datasets here. Or can do this on demand
# Verify results
file_list = join_dir.list_files()
print("Length Joint", len(file_list))
from diffgram import Project
project = Project(project_string_id="replace_with_project_string",
client_id="replace_with_client_id",
client_secret="replace_with_client_secret")
brain = project.get_model(name="my_model")
brain.check_status()
print(brain.status)
from diffgram import Project import settings """ Most minimal example of creating and launching a new job. """ project = Project( project_string_id = "replace_with_project_string", client_id = "replace_with_client_id", client_secret = "replace_with_client_secret" ) path = "file_path" file = project.file.from_local(path) job = project.job.new( name = "my job from SDK", file_list = [file], launch = True )
from diffgram import Project
project = Project(project_string_id="replace_with_project_string",
client_id="replace_with_client_id",
client_secret="replace_with_client_secret")
# Replace with your brain name, or leave blank to get latest
# Must set local flag to True
brain = project.get_model(name=None, local=True)
# Local, replace with yoru path
path = "A:/Sync/work/20190311_200900.jpg"
inference = brain.predict_from_local(path)
instance = inference.instance_list[0]
print(instance.location)
print(instance.score)
print(instance.label)
from diffgram import Project
project = Project(project_string_id="replace_with_project_string",
client_id="replace_with_client_id",
client_secret="replace_with_client_secret")
project.set_directory_by_name("directory_name")
path = "file_path"
file = project.file.from_local(path)
print(file.id)
import numpy as np
from scipy.misc import imsave
"""
Example of predicting locally from webcam
-> using two different brains
-> displays results live using matplotlib
-> saves images to directory for review
"""
project = Project(client_id=settings.CLIENT_ID,
client_secret=settings.CLIENT_SECRET,
project_string_id=settings.PROJECT_STRING_ID,
debug=False)
page_brain = project.get_model(name="page", local=True)
graphs_brain = project.get_model(name="graphs_three", local=True)
SAVE_IMAGES = True
# TODO optional to use temp directory
#temp = tempfile.mkdtemp()
#directory = temp + "/" + str(time.time()) + "/"
directory = str(time.time())
if not os.path.exists(directory):