Welcome to SeeMe.ai

SeeMe.ai is a no/low code MLOps platform aiming to be the simplest way you create, use, and share AI.

You can use SeeMe.ai without any code to automate the full AI lifecycle of your datasets and models.

The Python SDK gives easy access to all of your datasets, models, jobs, ... on the platform.

Installation

$ pip install seeme

Getting started

from seeme import Client

cl = Client()

# -- Registration --
my_username =    # example: "my_username"
my_email =       # example: "jan.vandepoel@seeme.ai"
my_password =    # example: "supersecurepassword"
my_firstname =   # example: "Jan"
my_name =        # example: "Van de Poel"

cl.register(
    username=my_username, 
    email=my_email, 
    password=my_password, 
    firstname=my_firstname, 
    name=my_name
)

# -- Log in --
cl.login(username, password)

# -- Log out --
cl.logout()

Datasets

Manage the entire lifecyle of your datasets:

create
manage
version
label
annotate
import/export

from seeme import DATASET_CONTENT_TYPE_IMAGES

# -- Get datasets --
datasets = cl.get_datasets()

my_dataset = {
    "name": "Cloud classifier",
    "description": "Classify clouds from pictures",
    "default_splits": True, # If `True`, adds 'train', 'valid', and 'test' default_splits
    "content_type": DATASET_CONTENT_TYPE_IMAGES,
    "multi_label": False
}

my_dataset = cl.create_dataset(my_dataset)

Checkout the dataset documentation to see all possibilities and detailed guides.

Models

Manage the entire lifecycle of your AI models:

create
managem
version
converst
predicti
import/export

# -- Get models --
models = cl.get_models()

# -- Application ID --
application_id = cl.get_application_id(
    base_framework="pytorch",
    framework="fastai",
    base_framework_version=str(torch.__version__),
    framework_version=str(fastai.__version__),
    application="image_classification"
)

# -- Create model --
model_name = "Cloud classifier"
description = "Classify clouds from images"

my_model = cl.create_model(  {
    "name": model_name,
    "description": description,
    "application_id": application_id,
    "auto_convert": True # Automatically converts your model to ONNX, CoreML, and TensorFlow Lite.
})

cl.upload_model(my_model["id"], model_file_location)

cl.inference(my_model["id"], image_location)

Checkout the [model] documentation](https://docs.seeme.ai/python-sdk/#models) to see all possibilities and detailed guides.

Jobs

Schedule training, validation, and model conversion jobs with a simple command:

from seeme import JOB_TYPE_TRAINING

jobs = cl.get_jobs()

job = {
    "name": "v3 image classifier",
    "description": "A new dataset for an improved model",
    "status_message": "",
    "application_id": application_id,
    "job_type": JOB_TYPE_TRAINING,
    "dataset_id": dataset_id,
    "dataset_version_id": datset_version_id,
    "model_id": model_id,
    "model_version_id": model_version_id,
    "items": [
      {
        "name": "image_size",
        "value": "224",
        "value_type": "number"
      },
      {
        "name": "arch",
        "value": "resnet50",
        "value_type": "text"
      }
    ]
  }

Applications

SeeMe.ai automates the full lifecycle of data and models for a wide range of AI applications, such as:

image classification
object detection
structured data
language models
multi lingual text classification
object character recognition (OCR)
named entity recognition (NER)

for a number of AI frameworks and their versions:

For a full list of frameworks and their versions:

# -- Get applications --
all_applications = cl.get_applications()

print(all_applications)

SDK Documentation

For more detailed SDK documentation see https://docs.seeme.ai.

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