Agent-Crop

Agent Crop is a Crop Disease detection and Cure suggestion system. It also provides details about the symptoms and the description of the particular disease.

The link for the Pre-Trained Model can be found in the app.py file.
The API can be accessed at the endpoint: https://agentcrop.azurewebsites.net/api/predict
The API request should have 'files' part and should only include png and jpg/jpeg files of size less than 50 MB.

Implement API in your App

<!DOCTYPE html>
<html>
    <body>
        <form action="https://agentcrop.azurewebsites.net/api/predict" method = "POST" enctype = "multipart/form-data" id="api-form">
            <input type="file" name="files" multiple required />
            <input type="submit" value="submit" />
        </form>
        <div id="show-data"></div>
        <script>
            // Function to work with your data.
            function workWithData(data) {

                // Here you can simply show data using iterating through it or you can do whatever you want with it.
                document.getElementById('show-data').innerHTML = "";
                for (let imageName in data) {
                    document.getElementById('show-data').innerHTML += "<h3>" + imageName + ": </h3>";
                    for (let detail in data[imageName]) {
                        document.getElementById('show-data').innerHTML += "<p><strong>" + detail.replace(detail[0], detail[0].toUpperCase()) + ": </strong>" + data[imageName][detail] + "</p>";
                    }
                }
            }

            // Function to handle submit event.
            function handleFormSubmit(event) {
                
                // Prevent default behavior of submit event.
                event.preventDefault();

                // Get the form element and url.
                const form = event.currentTarget;
                const url = form.action;
                
                // Define formData object to store the images and later send it to API.
                const formData = new FormData();

                // Find file input element.
                const photos = document.querySelector('input[type="file"][multiple]');
                
                // Iterate through file input element and save images to the formData object.
                for (let i = 0; i < photos.files.length; i++) {
                    formData.append('files', photos.files[i]);
                }

                // Below we use fetch to send formData to the API.
                fetch(url, {
                    method: 'POST',
                    body: formData,
                    origin: "*"
                })
                .then(
                    // After that we get response and work with it.
                    function(response) {

                        // If response's ok property is false, then shows error and return.
                        if (!response.ok) {
                            console.log('Looks like there was a problem. Status Code: ' + response.status);
                            return;
                        }

                        // Now we parse response to the json and then get the data object.
                        response.json().then(function(data) {

                            // We will pass data object to external function to work with it.
                            workWithData(data);
                        });
                    }
                )
                .catch(function(err) {
                    
                    // If any error occurs the it will show it.
                    console.log('Fetch Error :-S', err);
                });
            }

            // Get the form element using it's id.
            const apiForm = document.getElementById("api-form");

            // Add event listener on submit event.
            apiForm.addEventListener("submit", handleFormSubmit);
        </script>
    </body>
</html>

The API returns the json response in the following format:

{
    "image_1": {
        "description": "description_1",
        "prediction": "prediction_1",
        "source": "source_link_1",
        "symptoms": "symptoms_1"
    },
    "image_2": {
        "description": "description_2",
        "prediction": "prediction_2",
        "source": "source_link_2",
        "symptoms": "symptoms_2"
    }
}

List of Crops and Diseases supported

Apple
- Apple Scab
- Black Rot
- Cedar Rust
- Healthy
Blueberry
- Healthy
Cherry
- Powdery Mildew
- Healthy
Corn (Maize)
- Grey Leaf Spot
- Common Rust of Maize
- Northern Leaf Blight
- Healthy
Grape
- Black Rot
- Black Measles (Esca)
- Leaf Blight (Isariopsis Leaf Spot)
- healthy
Orange
- Huanglongbing (Citrus Greening)
Peach
- Bacterial spot
- healthy
Bell Pepper
- Bacterial Spot
- Healthy
Potato
- Early Blight
- Late Blight
- Healthy
Raspberry
- Healthy
Rice
- Brown Spot
- Hispa
- Leaf Blast
- Healthy
Soybean
- Healthy
Squash
- Powdery Mildew
Strawberry
- Leaf Scorch
- Healthy
Tomato
- Bacterial Spot
- Early Blight
- Late Blight
- Leaf Mold
- Septoria Leaf Spot
- Spider Mites (Two-spotted Spider Mite)
- Target Spot
- Yellow Leaf Curl Virus
- Mosaic Virus
- Healthy

victoryeovil/Plant_Diseases_Recognition

Agent-Crop