Develop Reference

Use LoadModelFromMemoy in ASSIMP to load obj model with no texture loaded

I'm currently working on an Android project where I need to load .obj file with ASSIMP on Android Platform. My way of implementing that is to use the AssetManager to load the .obj file into memory first, and then using the importer.ReadFileFromMemory() function to create the aiScene object. I've managed to import all vertex data, but I found that the texture is missing. I actually read from the ASSIMP GitHub page where it mentioned that ReadFileFromMemory() won't read contents cross file, therefore I think it is not reading the .mtl file where texture is applied. I would like to use the importer.ReadFile() function, but I have no idea on how to work with it on Android platform. Any one has suggestions?
Attached is my implementation of the loadModelFromMemory, similar as the loadModel from LearnOpenGL.
void Model::loadModelFromMemory(const void* pbuffer, size_t pLength)
{
Log::Message("Enter loadModelFromMemory", LOG_INIT);
// read file via ASSIMP
Assimp::Importer importer;
const aiScene* scene = importer.ReadFileFromMemory(pbuffer, pLength, aiProcess_Triangulate | aiProcess_GenSmoothNormals | aiProcess_FlipUVs | aiProcess_CalcTangentSpace);
// check for errors
if(!scene || scene->mFlags & AI_SCENE_FLAGS_INCOMPLETE || !scene->mRootNode) // if is Not Zero
{
Log::Message(strcat("ERROR::ASSIMP::", importer.GetErrorString()), LOG_ERROR);
return;
}
// process ASSIMP's root node recursively
processNode(scene->mRootNode, scene);
}
I have tried on using ReadFile but it is not working on the Android context. I also tried to use the MemoryIOWrapper provided by the ASSIMP, but have no clue on where to start.

There are different ways how to implement this.
Load the mtl- and the obj-file via memory buffers
Use the android-filesystem implementations to load assets from the asset-folder on your mobile phone. You can find our headers for that at Android File system implementations

Loading glb model in react native three using expo-three component not working on android device. The model appears on the web version though

I'm trying to create a react-native apps with three js using expo-gl, expo-three frameworks.
Following is the list of imports..
import { ExpoWebGLRenderingContext, GLView } from 'expo-gl';
import ExpoTHREE, { Renderer, TextureLoader } from 'expo-three';
import { GLTFLoader } from 'three/examples/jsm/loaders/GLTFLoader';
import * as React from 'react';
import {
AmbientLight,
HemisphereLight,
BoxBufferGeometry,
Fog,
GridHelper,
Mesh,
MeshStandardMaterial,
PerspectiveCamera,
PointLight,
Scene,
SpotLight,
Camera,
InstancedMesh,
} from 'three';
import OrbitControlsView from 'expo-three-orbit-controls';
Apart from the basic scene, camera and light setup I'm trying to load a glb model using the ExpoTHREE.loadAsync method as below...
const loadGlb = async ()=>{
const obj = await ExpoTHREE.loadAsync(
[require('./assets/suzanne.glb')],
null,
null}).
then((e)=>{
scene.add(e.scene);
e.scene.traverse((f)=>{if(f.isMesh){f.material = new THREE.MeshNormalMaterial();}});
})
.catch((err)=>{console.log(err)});
}
loadGlb();
Using the ref: https://www.npmjs.com/package/expo-three
The model loads when I run the code on the desktop browser but not on my android phone using expo app. Please let me know what am I doing wrong.
You can access the app here https://expo.io/#praful124/expo3

I had the same problem and ended up running into the fact that it does not support textures inside the glb file. But if you find a solution, I will be very happy if you share them.

Error in saving and using model of TensorForestEstimator for Android

I use the randomforest estimator, implemented in tensorflow, to predict if a text is english or not. I saved my model (A dataset with 2k samples and 2 class labels 0/1 (Not English/English)) using the following code (train_input_fn function return features and class labels):
model_path='test/'
TensorForestEstimator(params, model_dir='model/')
estimator.fit(input_fn=train_input_fn, max_steps=1)
After running the above code, the graph.pbtxt and checkpoints are saved in the model folder. Now I want to use it on Android. I have 2 problems:
As the first step, I need to freeze the graph and checkpoints to a .pb file to use it on Android. I tried freeze_graph (I used the code here: https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/tools/freeze_graph.py). When I call the freeze_graph in my mode, I get the following error and the code cannot create the final .pb graph:
File "/Users/XXXXXXX/freeze_graph.py", line 105, in freeze_graph
_ = tf.import_graph_def(input_graph_def, name="")
File "/anaconda/envs/tensorflow/lib/python2.7/site-packages/tensorflow/python/framework/importer.py", line 258, in import_graph_def
op_def = op_dict[node.op]
KeyError: u'CountExtremelyRandomStats'
this is how I call freeze_graph:
def save_model_android():
checkpoint_state_name = "model.ckpt-1"
input_graph_name = "graph.pbtxt"
output_graph_name = "output_graph.pb"
checkpoint_path = os.path.join(model_path, checkpoint_state_name)
input_graph_path = os.path.join(model_path, input_graph_name)
input_saver_def_path = None
input_binary = False
output_node_names = "output"
restore_op_name = "save/restore_all"
filename_tensor_name = "save/Const:0"
output_graph_path = os.path.join(model_path, output_graph_name)
clear_devices = True
freeze_graph.freeze_graph(input_graph_path, input_saver_def_path,
input_binary, checkpoint_path,
output_node_names, restore_op_name,
filename_tensor_name, output_graph_path,
clear_devices, "")
I also tried the freezing on the iris dataset in "tf.contrib.learn.datasets.load_iris". I get the same error. So I believe it is not related to the dataset.
As a second step, I need to use the .pb file on the phone to predict a text. I found the camera demo example by google and it contains a lot of code. I wonder if there is a step by step tutorial how to use a Tensorflow model on Android by passing a feature vector and get the class label.
Thanks, in advance!
UPDATE
By using the recent version of tensorflow (0.12), the problem is solved. However, now, the problem is that what I should pass to output_node_names ??? How can I get what are the output nodes in the graph ?

Re (1) it looks like you are running freeze_graph on a build of tensorflow which does not have access to contrib ops. Maybe try explicitly importing tensorforest before calling freeze_graph?
Re (2) I don't know of a simpler example.

CountExtremelyRandomStats is one of TensorForest's custom ops, and exists in tensorflow/contrib. As was pointed out, TF switched to including contrib ops by default at some point. I don't think there's an easy way to include the contrib custom ops in the global registry in the previous releases, because TensorForest uses the method of building a .so file that is included as a data file which is loaded at runtime (a method that was the standard when TensorForest was created, but may not be any longer). So there are no easily-included python build rules that will properly link in the C++ custom ops. You can try including tensorflow/contrib/tensor_forest:ops_lib as a dep in your build rule, but I don't think it will work.
In any case, you can try installing the nightly build of tensorflow. The alternative includes modifying how tensorforest custom ops are built, which is pretty nasty.

How do I load an image to an apk in delphi XE8

I am working on an app in Delphi XE8.
When I run the program on my phone, it gives me an error:
Loading bitmap failed(image.png)
My code works as follows:
if ListBox1.ItemIndex = 0 then
begin
img.bitmap.LoadFromFile('Image.png');
iMin:= Round(iNumber * 1);
iMax:= Round(iNumber *13.24);
iAvg:= Round(iNumber * 2.59);
label7.Text:= inttostr(iMin);
label5.Text:= inttostr(iAvg);
label6.Text:= inttostr(iMax);
label2.Text:= 'Minimum';
label3.Text:= 'Average';
label4.Text:= 'Maximum';
end
else
...
Please note the image is saved in the same folder as my program.

Don't use relative paths. Always use absolute paths.
You need to use the Deployment Manager to deploy the image file to an appropriate folder on the phone, and then use the System.IOUtils.TPath class to locate that folder at runtime:
Standard RTL Path Functions across the Supported Target Platforms
On Android, deploy the image file to the ./assets/internal folder, and then use the TPath.GetDocumentsPath() method at runtime, as documented on this blog:
Deploying and accessing local files on iOS and Android
What the EDN documentation and blog both fail to mention is that you also need to add the System.StartupCopy unit to your app's uses clause.
uses
..., System.IOUtils, System.StartupCopy;
...
img.bitmap.LoadFromFile(TPath.Combine(TPath.GetDocumentsPath, 'Image.png'));

Show image in TImage dynamically (at run time) without opendialog in c++ builder xe8

I want to show image (png,jpg etc) in dynamically created (as per requirement and fully through coding) TImage component, at runtime in C++ builder xe8 (not delphi). But I dont want to use opendialogbox (suggested in many web sites). I want to run this app on my android device. I tried to use LoadFromFile(), it crashes the app on android, but when I run this on windows, its running smoothly. I am just a beginner to c++ builder. So guys pls help. Thanx in advance for any kind of help.Here is what I did.
void __fastcall TForm1::TForm1(TComponent* Owner)
{
TImage* img = new TImage(this);
img->Parent = this;
img->Bitmap->LoadFromFile("D:\\res\\profile.png");
}

Did you see what is the error?
If you run the program with the provided by you code I assume the error would be that the file is not found, because there is no such directory "D:\" in android.
One way to set the path is to write a static path which points to your image. For example : "/storage/sdcard0/DCIM/Camera/MyImage.jpg";
The second way is to include the <System.IOUtils.hpp> header and to use some built-in functions like:
System::Ioutils::TPath::GetPicturesPath();
System::Ioutils::TPath::GetAlarmsPath();
You can check them out, they might be useful.