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from flask import Flask
from flask import request
app = Flask(__name__)
@app.route('/get-img', methods = ['POST'])
def get():
if request.method == 'POST':
arg1=request.get_json()['url']
@app.route('/')
def home():
return "hello world"
# app.run()
# %%
import tensorflow
import pickle
import cv2
import numpy as np
from tensorflow.keras.models import load_model
def pridict (url):
instance=pickle.load(open(r"Label_Instance.pkl","rb"))
mod=load_model(r"model.h5")
img = cv2.imread(url)
img = cv2.resize(img,(256,256))
img = np.reshape(img,[1,256,256,3])
img=img/255.0
max_val=np.argmax(mod.predict(img))
label=instance.classes_[max_val]
return label
def test(url):
return url
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