AiForklift/magazine/views.py

import math
import json
from django.shortcuts import render
from django.http import HttpResponse
from django.views.decorators.csrf import csrf_exempt

import tensorflow as tf
import numpy as np
# Create your views here.


def index(request):
    return HttpResponse('It lives!')


@csrf_exempt
def classify(request):
    loaded_request = json.load(request)
    sw = loaded_request['sepalWidth']
    sl = loaded_request['sepalLength']
    pw = loaded_request['petalWidth']
    pl = loaded_request['petalLength']

    model = tf.keras.models.load_model('iris_model.h5')
    output = model.predict(np.array([[sw, sl, pw, pl]]))
    if output[0][0] > output[0][1] and output[0][0] > output[0][1]:
        guess = 1
    elif output[0][1] > output[0][0] and output[0][1] > output[0][2]:
        guess = 2
    else:
        guess = 3
    return HttpResponse(guess)


@csrf_exempt
def shortestPath(request):
    loaded_request = json.load(request)

    graph = loaded_request["graph"]
    graph = {int(k): v for k, v in graph.items()}
    for node in graph:
        graph[node] = {
            int(k): v for k, v in graph[node].items()}

    start_node = loaded_request["start_node"]
    dest_node = loaded_request["dest_node"]

    distance = {}
    predecessor = {}
    path = {}
    unseen_nodes = graph.copy()

    for node in graph:
        distance[node] = math.inf
    distance[start_node] = 0

    while unseen_nodes:
        min_node = None
        for node in unseen_nodes:
            if min_node is None:
                min_node = node
            elif distance[node] < distance[min_node]:
                min_node = node

        for childNode, weight in graph[min_node].items():
            if distance[min_node] + weight < distance[childNode]:
                distance[childNode] = distance[min_node] + weight
                predecessor[childNode] = min_node
        unseen_nodes.pop(min_node)

    for node in graph:
        current = node
        p = [current]
        while current != start_node:
            p.append(predecessor[current])
            current = predecessor[current]
        path[node] = p[::-1]

    print(path)

    return HttpResponse(path[dest_node][1:])