[update] retest & update readme for beginner

Author: BIGBALLON

README.md

@@ -1,60 +1,83 @@
-# pytorch_cpp
+
+
+<img src="./pic/pytorch-cpp.jpg" width=30% align="right" /> 
 
 This demo will show you how to use libtorch to build your C++ application.
 
+**[UPDATE 2020/02/22]** : Thanks for [Ageliss](https://github.com/Ageliss) and his [PR](https://github.com/BIGBALLON/PyTorch-CPP/pull/4), which update this demo to fit libtorch v1.4.0 and opencv4.0.  
+**[UPDATE 2020/04/15]** : Retest this tutorial with **OpenCV4.3**/**PyTorch1.4**/**LibTorch1.4**, update readme for beginner.
+
+
 ## Contents
 
-1. [Requirements](#requirements)
-2. [Build](#build)
-3. [Usage](#usage)
+- [Contents](#contents)
+- [Requirements](#requirements)
+- [Preparation](#preparation)
+  - [Step 0x00](#step-0x00)
+  - [Step 0x01](#step-0x01)
+  - [Step 0x02](#step-0x02)
+  - [Step 0x03](#step-0x03)
+- [Build](#build)
+- [Usage](#usage)
 
 
-## Requirements
+## Requirements 
 
-- Pytorch (tag: pytorch v1.0)
-- Libtorch
-- OpenCV
+- PyTorch (>= v1.4.0)
+- LibTorch (>= v1.4.0)
+- OpenCV (>= v4.0)
 
-## Build
+## Preparation
 
-### Step 1
 
-Export your pytorch model to torch script file, We will simply use resnet50 in this demo
+### Step 0x00
 
-### Step 2
+**Make sure** LibTorch and OpenCV have been installed correctly.
 
-Write your C++ program, check the file ``prediction.cpp`` for more detial.  
+- **Install OpenCV**: for [Linux](https://docs.opencv.org/4.3.0/d7/d9f/tutorial_linux_install.html), for [Mac OS](https://docs.opencv.org/4.3.0/d0/db2/tutorial_macos_install.html)
 
-PS: ``module->to(at::kCUDA)`` and ``input_tensor.to(at::kCUDA)`` will switch your model & tensor to GPU mode,  
-comment out them if you just want to use CPU mode. 
+- **Get LibTorch**: download [zip](https://pytorch.org/get-started/locally/) from PyTorch website, then unpack it.
 
+> **PS**: the version of OpenCV must the same as your libtorch. Otherwise, you may get the compile error: ``error: undefined reference to `cv::imread(std::string const&, int)'``, check [issues 14684](https://github.com/pytorch/pytorch/issues/14684) and [issues 14620](https://github.com/pytorch/pytorch/issues/14620) for more details.
 
-### Step 3
+### Step 0x01
 
-Write a ``CMakeLists.txt``, the version of OpenCV must the same as your libtorch.
-Otherwise, you may get the compile error:
+Export PyTorch model to torch script file(we use ``resnet50`` in this demo). See [model_trace.py](./model_trace.py).
 
-```
-error: undefined reference to `cv::imread(std::string const&, int)'
-```
+### Step 0x02
 
-check [issues 14684](https://github.com/pytorch/pytorch/issues/14684) and [issues 14620](https://github.com/pytorch/pytorch/issues/14620) for more details.
+Write C++ application program, check [prediction.cpp](./prediction.cpp) for more detials.  
+
+> **PS**: ``module->to(at::kCUDA)`` and ``input_tensor.to(at::kCUDA)`` will switch your model & tensor to GPU mode, comment out them if you just want to use CPU mode. 
 
-## Usage
 
-- run ``model_trace.py``,   then you will get a file ``resnet50.pt``
+### Step 0x03
+
+Write a [CMakeLists.txt](./CMakeLists.txt). check [cppdocs](https://pytorch.org/cppdocs/) for more details.
+
+## Build
+
+- run ``model_trace.py``, you will get a converted model ``resnet50.pt``.
 - compile your cpp program, you need to use ``-DCMAKE_PREFIX_PATH=/absolute/path/to/libtorch``, for example:
 
-```
+```bash
 mkdir build
 cd build
-cmake -DCMAKE_PREFIX_PATH=/home/cgilab/pytorch/torch/lib/tmp_install ..
+# change "/home/bigballon/libtorch" to your libtorch path
+cmake -DCMAKE_PREFIX_PATH=/home/bigballon/libtorch ..
 make
 ```
 
-- test your program
+## Usage
+
+
+```bash
+classifier <path-to-exported-script-module> <path-to-lable-file>
+# example:
+# ./classifier ../resnet50.pt ../label.txt
+```
 
-``classifier <path-to-exported-script-module> <path-to-lable-file>``
+![video](./pic/video.gif)
 
 ```
 > ./classifier ../resnet50.pt ../label.txt
@@ -76,7 +99,7 @@ make
     With Probability:  0.110916%
 == Input image path: [enter Q to exit]
 ```
-![](./pic/dog.jpg)
+![dog](./pic/dog.jpg)
 
 ```
 ../pic/shark.jpg
@@ -94,7 +117,7 @@ make
 == Input image path: [enter Q to exit]
 Q
 ```
-![](./pic/shark.jpg)
+![shark](./pic/shark.jpg)
 
 
-Take it easy!!
+Take it easy!! :love_letter:

model_trace.py

@@ -2,6 +2,7 @@
 import torchvision
 
 model = torchvision.models.resnet50(pretrained=True)
+# Don't forget change model to eval mode
 model.eval()
 example = torch.rand(1, 3, 224, 224)
 traced_script_module = torch.jit.trace(model, example)

pic/pytorch-cpp.jpg

@@ -58,7 +58,7 @@ int main(int argc, const char *argv[]) {
 
     torch::jit::script::Module module = torch::jit::load(argv[1]);
     std::cout << "== Switch to GPU mode" << std::endl;
-//  to GPU
+    // to GPU
     module.to(at::kCUDA);
 
     std::cout << "== ResNet50 loaded!\n";
@@ -108,4 +108,5 @@ int main(int argc, const char *argv[]) {
             std::cout << "Can't load the image, please check your path." << std::endl;
         }
     }
+    return 0;
 }