I’m trying to run a Python model in my React Native project using TensorFlow.js. The model I have is a ResNet50 model trained in Python. How can I integrate this model into my React Native project and use it for image prediction?
import streamlit as st
import os
from PIL import Image
import numpy as np
import pickle
import tensorflow
from tensorflow.keras.layers import GlobalMaxPooling2D
from tensorflow.keras.applications.resnet50 import ResNet50,preprocess_input
from sklearn.neighbors import NearestNeighbors
from numpy.linalg import norm
import cv2
feature_list = np.array(pickle.load(open('featurevector.pkl','rb')))
filenames = pickle.load(open('filenames.pkl','rb'))
model = ResNet50(weights='imagenet',include_top=False,input_shape=(224,224,3))
model.trainable = False
model = tensorflow.keras.Sequential([
model,
GlobalMaxPooling2D()
])
st.title('Man & Women Fashion Recommender System')
def save_uploaded_file(uploaded_file):
try:
with open(os.path.join('uploads',uploaded_file.name),'wb') as f:
f.write(uploaded_file.getbuffer())
return 1
except:
return 0
def extract_feature(img_path, model):
img=cv2.imread(img_path)
img=cv2.resize(img, (224,224))
img=np.array(img)
expand_img=np.expand_dims(img, axis=0)
pre_img=preprocess_input(expand_img)
result=model.predict(pre_img).flatten()
normalized=result/norm(result)
return normalized
def recommend(features,feature_list):
neighbors = NearestNeighbors(n_neighbors=6, algorithm='brute', metric='euclidean')
neighbors.fit(feature_list)
distances, indices = neighbors.kneighbors([features])
return indices
# steps
# file upload -> save
uploaded_file = st.file_uploader("Choose an image")
print(uploaded_file)
if uploaded_file is not None:
if save_uploaded_file(uploaded_file):
# display the file
display_image = Image.open(uploaded_file)
resized_img = display_image.resize((200, 200))
st.image(resized_img)
# feature extract
features = extract_feature(os.path.join("uploads",uploaded_file.name),model)
#st.text(features)
# recommendention
indices = recommend(features,feature_list)
# show
col1,col2,col3,col4,col5 = st.columns(5)
with col1:
st.image(filenames[indices[0][1]])
with col2:
st.image(filenames[indices[0][2]])
with col3:
st.image(filenames[indices[0][3]])
with col4:
st.image(filenames[indices[0][4]])
with col5:
st.image(filenames[indices[0][5]])
else:
st.header("Some error occured in file upload")
code looks like this.
Goal of the application is to provide 5 similar images based on the input image. I also want to use this for a clothing application but I’m not experienced in the field of artificial intelligence. Is anyone know how to convert the code?
