droplets Computer Vision Model
How to use the droplets 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="droplets-oa7e9/1")Or, Use Free Crossing and Droplet 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": "crossing, Droplet"
},
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 droplets Model
Here are a few use cases for this project:
-
Plumbing Repairs and Maintenance: The model could be used to detect and classifying droplet leakages in pipes, aiding in early detection of potential plumbing faults. Detecting crossing or merging droplets could indicate abnormal water flow patterns suggestive of pipeline issues.
-
Quality Control in Manufacturing Processes: In industries where droplets are used in production processes (like pharmaceutical, paint, or chemical industries), the model could be used to classify droplet behaviors - whether droplets are being dispensed correctly or if they're crossing, indicating potential defects or deviations in the production process.
-
Weather Research and Predictions: The model could be employed to study droplet formations and patterns on surfaces to understand their correlations with different weather phenomena. The "crossing" class could also indicate rain or mist situations that can be empirical data for weather analysis and predictions.
-
Medical Diagnostics: The model might assist in the analysis of biomedical samples, classifying different patterns of droplet formation or migration that could be indicative of certain diseases or conditions.
-
Agriculture and Irrigation: The model could be useful to optimize irrigation systems by understanding droplet dispersion patterns (including "crossing") and thereby minimizing water waste while maximizing crop water absorption.
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{ droplets-oa7e9_dataset,
title = { droplets Dataset },
type = { Open Source Dataset },
author = { wanglianggithub },
howpublished = { \url{ https://universe.roboflow.com/wanglianggithub/droplets-oa7e9 } },
url = { https://universe.roboflow.com/wanglianggithub/droplets-oa7e9 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { mar },
note = { visited on 2026-07-29 },
}