Object Detection and Visualization - Seeed Grove Vision AI Module

import subprocess
import time
# Replace the path with the actual path to edge-impulse-run-impulse executable
path_to_executable = 'edge-impulse-run-impulse'

# Replace output.txt with the desired name and path for your output file
output_file = open('output.txt', 'w')

# Launch the executable using subprocess and pipe the output to the output file
subprocess.Popen([path_to_executable], stdout=output_file)

# Continuously parse the output file for prediction results

import requests
import json

def send_to_ubidots(name, confidence):
    url = "https://industrial.api.ubidots.com/api/v1.6/devices/groveai"
    payload = {
        name: {
            "value": confidence,
        }
    }
    headers = {
        "Content-Type": "application/json",
        "X-Auth-Token": “ABCD-abcdefghijklmnopqrstuvwxyz”
    }
    response = requests.post(url, headers=headers, data=json.dumps(payload))
    return response.status_code

with open("output.txt", "r") as f:
    lines_seen = set()
    while True:
        line = f.readline()
        if not line:
            time.sleep(1)
            continue
        if ("Batman" in line or "Superman" in line) and line not in lines_seen:
            print(line)
            parts = line.split()
            name = parts[0]
            confidence = float(parts[1][1:-1])
            status_code = send_to_ubidots(name, confidence)
            if status_code != 200:
                print("Error sending data to Ubidots: status code {}".format(status_code))
            lines_seen.add(line)