Skip to main content

What this message mean? Trying to run a model that was trained in TeachableMachine

I try to run a python program but every time it shows this message:

I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN)to use the following CPU instructions in performance-critical operations: AVX AVX2 To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags. WARNING:tensorflow:No training configuration found in the save file, so the model was not compiled. Compile it manually.

The program that I use is:

from keras.models import load_model
from PIL import Image, ImageOps
import numpy as np

# Load the model
model = load_model('path/to/trained/model/keras_model.h5')

# Create the array of the right shape to feed into the keras model
# The 'length' or number of images you can put into the array is
# determined by the first position in the shape tuple, in this case 1.
data = np.ndarray(shape=(1, 224, 224, 3), dtype=np.float32)
# Replace this with the path to your image
image = Image.open('path/to/image/image.png')
#resize the image to a 224x224 with the same strategy as in TM2:
#resizing the image to be at least 224x224 and then cropping from the center
size = (224, 224)
image = ImageOps.fit(image, size, Image.ANTIALIAS)

#turn the image into a numpy array
image_array = np.asarray(image)
# Normalize the image
normalized_image_array = (image_array.astype(np.float32) / 127.0) - 1
# Load the image into the array
data[0] = normalized_image_array

# run the inference
prediction = model.predict(data)
print(prediction)

Both my CPU and GPU are AMD. What am I doing wrong?



source https://stackoverflow.com/questions/69397833/what-this-message-mean-trying-to-run-a-model-that-was-trained-in-teachablemachi
Labels:

Comments

Post a Comment

Popular posts from this blog

Why is my reports service not connecting?

I am trying to pull some data from a Postgres database using Node.js and node-postures but I can't figure out why my service isn't connecting. my routes/index.js file: const express = require('express'); const router = express.Router(); const ordersCountController = require('../controllers/ordersCountController'); const ordersController = require('../controllers/ordersController'); const weeklyReportsController = require('../controllers/weeklyReportsController'); router.get('/orders_count', ordersCountController); router.get('/orders', ordersController); router.get('/weekly_reports', weeklyReportsController); module.exports = router; My controllers/weeklyReportsController.js file: const weeklyReportsService = require('../services/weeklyReportsService'); const weeklyReportsController = async (req, res) => { try { const data = await weeklyReportsService; res.json({data}) console...
Post a Comment
Read more

How to show number of registered users in Laravel based on usertype?

i'm trying to display data from the database in the admin dashboard i used this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count(); echo $users; ?> and i have successfully get the correct data from the database but what if i want to display a specific data for example in this user table there is "usertype" that specify if the user is normal user or admin i want to user the same code above but to display a specific usertype i tried this: <?php use Illuminate\Support\Facades\DB; $users = DB::table('users')->count()->WHERE usertype =admin; echo $users; ?> but it didn't work, what am i doing wrong? source https://stackoverflow.com/questions/68199726/how-to-show-number-of-registered-users-in-laravel-based-on-usertype
Post a Comment
Read more

The number of nodes and edges I calculated manually and by a method provided by networkx library dont match

I am trying to analyse a graph using networkx library in Python. I have implemented a function that returns the nodes and edges of that graph. After that I counted the number of nodes and edges by implementing the len() function for nodes and edges, which gave me 17 for both nodes and edges. However, when I used the method graph.number_of_nodes() of networkx library it gave me 53. My code: import pandas as pd import networkx as nx import matplotlib.pyplot as plt header_list = ["a","b","w"] E =pd.read_csv("aves-barn-swallow-contact-network.edges",sep=" ",header= None,names=header_list) # print(E.head()) # prints first few rows of the csv file G = nx.from_pandas_edgelist(E,"a","b",["w"]) nx.draw(G) plt.show() class GraphAnalyse: #finding nodes and edges def nodeEdge(self,Graph): nodes = Graph.nodes() edges = Graph.edges() ...
Post a Comment
Read more