scrap-materials Computer Vision Dataset
How to use the scrap-materials Detection API
Try This Model
Drop an image here or click to upload
Or try a test image
Model type: Roboflow Instant
Dataset: scrap-materials/1 (387 images)
Model ID: janrells-workspace/motorcycle-block-instant-1
May 7, 2026
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="janrells-workspace/motorcycle-block-instant-1")Give your agent everything it needs
Or, Use Free Copper, Cylinder_block and Laptop_battery Detection API
Powered by general detection model
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": "copper, cylinder_block, laptop_battery, motorcycle_battery, motorcycle-block"
},
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
About scrap-materials Model
Scrap Material Data for Undergraduate Capstone Project
Roboflow Agent
Tell the agent what you want to build.
Cite This Project
LicenseCC BY 4.0If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{ scrap-materials_dataset,
title = { scrap-materials Dataset },
type = { Open Source Dataset },
author = { Janrells Workspace },
howpublished = { \url{ https://universe.roboflow.com/janrells-workspace/scrap-materials } },
url = { https://universe.roboflow.com/janrells-workspace/scrap-materials },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2026 },
month = { jun },
note = { visited on 2026-07-29 },
}










