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HOW TO HANDLE THIS ERROR: "Failed to get input map for signature: serving_default"

import requests
import json
import numpy as np
import base64
import cv2

# Replace this with the actual image path you want to test
image_path = 'H_L_.jpg'

# Read and preprocess the image
image = cv2.imread(image_path)
image = cv2.resize(image, (256, 256))
image = image.astype(np.float32) / 255.0
image = np.expand_dims(image, axis=0)

# Convert the NumPy array to bytes before encoding
encoded_image = base64.b64encode(image.tobytes()).decode('utf-8')

# Prepare the JSON request with the signature name
data = {
    "signature_name": "serving_default",
    "instances": [{"input_1": encoded_image}]  # Adjust the input key based on your model's signature
}
# Replace these labels with your actual labels
labels = ['Potato___Early_blight', 'Potato___Late_blight', 'Potato___healthy']

# Send the inference request to TensorFlow Serving
url = 'http://localhost:8501/v1/models/model:predict'  # Replace 'model' with the actual model name and version
headers = {"content-type": "application/json"}
response = requests.post(url, data=json.dumps(data), headers=headers)

# Process the response
if response.status_code == 200:
    predictions = response.json()['predictions'][0]
    predicted_class_idx = np.argmax(predictions)
    predicted_label = labels[predicted_class_idx]
    print("Predicted Label:", predicted_label)
    print("Class Probabilities:", predictions)
else:
    print("Error: Unable to get predictions. Status code:", response.status_code)
    print("Response content:", response.content)