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wheat-plants-in-crop/3 (latest)
How to Use the Wheat Plants In Crop Detection API
Use this pre-trained Wheat Plants In Crop computer vision model to retrieve predictions with our hosted API or deploy to the edge. Learn More About Roboflow Inference
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Model:
mAP is equal to the average of the Average Precision metric across all classes in a
model.
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mAP
Samples from Test Set
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fps
0
objects detected
Roboflow Inference
Inference is Roboflow's open source deployment package for developer-friendly vision inference.
How to Deploy the Wheat Plants In Crop Detection API
Using Roboflow, you can deploy your object detection model to a range of environments, including:
- Raspberry Pi
- NVIDIA Jetson
- A Docker container
- A web page
- A Python script using the Roboflow SDK.
Below, we have instructions on how to use our deployment options.
Code Snippets
Python
JavaScript
Infer on Local and Hosted Images
To install dependencies, pip install inference-sdk.
Then, add the following code snippet to a Python script:
from inference_sdk import InferenceHTTPClient
CLIENT = InferenceHTTPClient(
api_url="https://outline.roboflow.com",
api_key="API_KEY"
)
result = CLIENT.infer(your_image.jpg, model_id="wheat-plants-in-crop/2")
Node.js
We're using axios to perform the POST request in this example so first run npm install axios to install the dependency.
Inferring on a Local Image
const axios = require("axios");
const fs = require("fs");
const image = fs.readFileSync("YOUR_IMAGE.jpg", {
encoding: "base64"
});
axios({
method: "POST",
url: "https://outline.roboflow.com/wheat-plants-in-crop/2",
params: {
api_key: "API_KEY"
},
data: image,
headers: {
"Content-Type": "application/x-www-form-urlencoded"
}
})
.then(function (response) {
console.log(response.data);
})
.catch(function (error) {
console.log(error.message);
});
Inferring on an Image Hosted Elsewhere via URL
const axios = require("axios");
axios({
method: "POST",
url: "https://outline.roboflow.com/wheat-plants-in-crop/2",
params: {
api_key: "API_KEY",
image: "IMAGE_URL"
}
})
.then(function (response) {
console.log(response.data);
})
.catch(function (error) {
console.log(error.message);
});
More Deployment Resources
Roboflow Inference Documentation
Look through our Inference documentation for more information and resources on how to utilize this model.
Example Web App
Use this model with a full fledged web application that has all sample code included.
Deploy to NVIDIA Jetson
Perform inference at the edge with a Jetson via our Docker container.
Deploy Mobile iOS
Utilize your model on your mobile device.
