Universe

fassto_box Computer Vision Model

byfasstoTask:
Instance Segmentation
License:CC BY 4.0106 views16 downloads

How to use the fassto_box Segmentation API

Try This Model

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Code Snippets

from inference_sdk import InferenceHTTPClient

CLIENT = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key="API_KEY"
)

result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="fassto_box/5")
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Code
pip install inference-sdk
# 1. Import the library
from inference_sdk import InferenceHTTPClient

# 2. Connect to your workspace
client = InferenceHTTPClient(
  api_url="https://serverless.roboflow.com",
  api_key="API_KEY"
)

# 3. Run your workflow on an image
result = client.run_workflow(
  workspace_name="<YOUR_WORKSPACE>",
  workflow_id="<YOUR_WORKFLOW_ID>",
  images={
    "image": "YOUR_IMAGE.jpg"  # Path to your image file
  },
  parameters={
    "classes": "sku"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Run on custom image

Drop an image here or click to upload

Detecting classes:
Or try a test image 
See all 815 imagesfassto_box sku samplefassto_box sku samplefassto_box sku samplefassto_box sku samplefassto_box sku samplefassto_box sku samplefassto_box sku sample showing skufassto_box sku samplefassto_box sku samplefassto_box sku samplefassto_box sku samplefassto_box sku sample

About fassto_box Model

Here are a few use cases for this project:

  1. Inventory Management: The "fassto_box" model can be useful in managing inventory in warehouses or retail stores. It could be implemented to automatically identify and track the SKU of each product, thereby improving the speed and accuracy of inventory counts.

  2. E-commerce Fulfillment: This computer vision model could facilitate accurate order fulfillment in e-commerce facilities. By identifying and verifying SKU classes on packaged items, the model could help minimize packing errors and ensure customers receive the correct products.

  3. Quality Control: The model can be used to automate quality control processes in manufacturing and packaging industries. It could quickly identify incorrect SKU tags on packaged items, reducing the risk of shipping errors or customer dissatisfaction.

  4. Recycling and Waste Management: The model can be applied in recycling facilities to classify different products based on their SKU. The ability to identify specific food items in boxed packaging could help in sorting recyclable materials more efficiently.

  5. Retail Shelves Replenishment: "fassto_box" model can automate the process of restocking items on retail shelves. By identifying the SKU class of missing items, the model could assist staff in replenishing products effectively, leading to improved store management and enhanced customer shopping experiences.

Cite This Project

LicenseCC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{ fassto_box_dataset,
  title = { fassto_box Dataset },
  type = { Open Source Dataset },
  author = { fassto },
  howpublished = { \url{ https://universe.roboflow.com/fassto/fassto_box } },
  url = { https://universe.roboflow.com/fassto/fassto_box },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { mar },
  note = { visited on 2026-07-29 },
}

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