Notes

from flask import Flask, request, jsonify, render_template
import cv2
import base64
import numpy as np
import os
import requests
from roboflow import Roboflow
import time

app = Flask(__name__)

# গ্লোবাল ভেরিয়েবল ডিটেকশন স্টেট ট্র্যাক করার জন্য
last_detection_time = 0
detection_cooldown = 2 # 2 সেকেন্ড কো-লডাউন পিরিয়ড

# Roboflow সেটআপ
rf = Roboflow(api_key="GiFvO4SzDxqs4Jv9fTiE")
project = rf.workspace().project("smart-dustbin-yhsey")
model = project.version(1).model

# অবজেক্ট কাউন্টার
object_counts = {
'plastic': 0,
'metal': 0,
'organic': 0,
'drywaste': 0

}

backend_url = 'http://127.0.0.1:8000/api/detect/'

@app.route('/')
def index():
return render_template('index.html')

@app.route('/predict', methods=['POST'])
def predict():
global last_detection_time

current_time = time.time()

# কো-লডাউন পিরিয়ড চেক করা
if current_time - last_detection_time < detection_cooldown:
return jsonify({
"status": "cooldown",
"message": f"Waiting {detection_cooldown} seconds between detections"
}), 200

data = request.get_json()
if 'image' not in data:
return jsonify({'error': 'No image provided'}), 400

image_data = data['image'].split(',')[1]
image_bytes = base64.b64decode(image_data)

np_arr = np.frombuffer(image_bytes, np.uint8)
img = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)

temp_filename = "frame.jpg"
cv2.imwrite(temp_filename, img)

# কনফিডেন্স লেভেল 50 এ সেট করা
prediction = model.predict(temp_filename, confidence=50, overlap=30).json()
predictions = prediction.get("predictions", [])

global object_counts
object_counts = {k: 0 for k in object_counts}

for det in predictions:
class_name = det['class'].lower()
if class_name in object_counts:
object_counts[class_name] += 1

result = {
"predictions": predictions,
"total_objects": sum(object_counts.values()),
"object_counts": object_counts
}

# শুধুমাত্র প্রথম ডিটেক্টেড অবজেক্ট প্রসেস করা
if sum(object_counts.values()) > 0:
send_first_detected_object(object_counts)
last_detection_time = time.time() # শেষ ডিটেকশনের টাইম আপডেট করা

if os.path.exists(temp_filename):
os.remove(temp_filename)

return jsonify(result)

def send_first_detected_object(object_counts):
priority_order = ['plastic', 'metal', 'drywaste', 'organic']

detected_class = None
count = 0

for class_name in priority_order:
if object_counts.get(class_name, 0) > 0:
detected_class = class_name
count = object_counts[class_name]
break

if not detected_class:
print("No objects detected to send to backend")
return

data = {
'detected_class': detected_class,
'count': count
}

try:
response = requests.post(backend_url, json=data)
print(f"Sent data to backend: {response.status_code} {response.text}")
except Exception as e:
print(f"Error sending data to backend: {e}")

if __name__ == '__main__':
app.run(debug=True)

# app.run(host='"
and views.py"from rest_