pv-segmentation Computer Vision Model
How to use the pv-segmentation Detection API
Try This Model
Drop an image here or click to upload
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="pv-segmentation-ap5gi/4")Or, Use Free Solar_cell Detection API
Powered by general detection model
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": "solar_cell"
},
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
About pv-segmentation Model
Here are a few use cases for this project:
-
Solar Panel Inspection and Maintenance: The pv-segmentation model can be used to identify solar cells within solar panels, allowing for efficient detection of faulty or damaged cells. This could facilitate more effective maintenance schedules and ultimately improve the overall performance of solar power systems.
-
Solar Panel Manufacturing and Quality Control: The model can be utilized as an automated quality control check during the manufacturing process. By identifying pv-cell classes accurately, it can verify that solar cells are properly aligned and assembled, helping to ensure that high-quality panels are produced.
-
Energy Production Forecasting: Accurate identification of solar_cell class can help researchers and manufacturers calculate the capacity and efficiency of a specific solar panel or solar power system. This information can be used to develop more accurate energy production forecasts and assess the potential of different solar technologies.
-
Remote Monitoring of Solar Installations: The model can be used to analyze aerial or satellite imagery of large-scale solar installations. This allows for remote monitoring of solar panel performance, assessment of potential expansion or upgrade opportunities, and rapid identification of any maintenance needs.
-
Solar Panel Recycling and Repurposing: By accurately identifying pv-cell classes, the pv-segmentation model could assist in sorting and separating solar cells during the recycling process. This could enable more efficient recycling of materials and encourage the repurposing of solar cells on the second-hand market.
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{ pv-segmentation-ap5gi_dataset,
title = { pv-segmentation Dataset },
type = { Open Source Dataset },
author = { Clean Energy Associate },
howpublished = { \url{ https://universe.roboflow.com/clean-energy-associate/pv-segmentation-ap5gi } },
url = { https://universe.roboflow.com/clean-energy-associate/pv-segmentation-ap5gi },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { mar },
note = { visited on 2026-07-29 },
}