![](https://github.com/darrenyao87/tnn-models/raw/master/doc/cn/user/resource/convert.png)
TNN currently supports the industry's mainstream model file formats, including ONNX, Pytorch, Tensorflow and Caffe. As shown in the figure above, TNN utilizes ONNX as the intermediate port to support multiple model file formats.
To convert model file formats such as Pytorch, Tensorflow, TensorFlow-Lite, and Caffe to TNN, you need to use corresponding tool to convert from the original format to ONNX model first, which then will be transferred into a TNN model.
diff --git a/doc/en/user/demo_en.md b/doc/en/user/demo_en.md
index 6cfa30a41..9eab95f1f 100644
--- a/doc/en/user/demo_en.md
+++ b/doc/en/user/demo_en.md
@@ -47,14 +47,14 @@
Click the TNNExamples project as shown below, find the project setting `Signing & Capabilities`, click the Team tab and select `Add an Account...`
-
![](https://gitee.com/darren3d/tnn-resource/raw/master/doc/cn/user/resource/ios_add_account_demo.jpg)
+
![](https://github.com/darrenyao87/tnn-models/raw/master/doc/cn/user/resource/ios_add_account_demo.jpg)
Enter the Apple ID account and password in the following interface. Return to the `Signing & Capabilities` interface, and select the added account in the Team tab. If you don’t have an Apple ID, you can also use the “Create Apple ID” option to apply according to the relevant prompts.
`PS: There is no fee to apply for Apple ID, it can be passed immediately, and the APP can be run on the real machine after debugging.`
-
![](https://gitee.com/darren3d/tnn-resource/raw/master/doc/cn/user/resource/ios_set_account.jpg)
+
![](https://github.com/darrenyao87/tnn-models/raw/master/doc/cn/user/resource/ios_set_account.jpg)
4. Run on real machine
@@ -63,14 +63,14 @@
As shown in the figure, after the existing `Bundle Identifier`, a suffix (limited to numbers and letters) is randomly added to avoid personal account conflicts.
-
![](https://gitee.com/darren3d/tnn-resource/raw/master/doc/cn/user/resource/ios_set_bundleid_demo.jpg)
+
![](https://github.com/darrenyao87/tnn-models/raw/master/doc/cn/user/resource/ios_set_bundleid_demo.jpg)
4.2 Verify authorization
For the first time, use the shortcut key `Command + Shift + K` to clean up the project, and then execute the shortcut key` Command + R` to run. If it is the first time to log in with Apple ID, Xcode will pop up a box and report the following error. You need to verify the authorization on the iOS device according to the prompt. Generally speaking, the authorization path on the phone is: Settings-> General-> Profile and Device Management-> Apple Development Options-> Click Trust
-
![](https://gitee.com/darren3d/tnn-resource/raw/master/doc/cn/user/resource/ios_verify_certificate_demo.jpg)
+
![](https://github.com/darrenyao87/tnn-models/raw/master/doc/cn/user/resource/ios_verify_certificate_demo.jpg)
4.3 Result
@@ -94,7 +94,7 @@
Effect example: iPhone 7, ARM single thread 6.3206ms
-
![](https://gitee.com/darren3d/tnn-resource/raw/master/doc/cn/user/resource/face_detector.jpg)
+
![](https://github.com/darrenyao87/tnn-models/raw/master/doc/cn/user/resource/face_detector.jpg)
2. Image classification
@@ -102,7 +102,7 @@
Example: iPhone 7, ARM single thread 13.83ms
-
![](https://gitee.com/darren3d/tnn-resource/raw/master/doc/cn/user/resource/image_classify.jpg)
+
![](https://github.com/darrenyao87/tnn-models/raw/master/doc/cn/user/resource/image_classify.jpg)
## II. Introduction to Android Demo
@@ -175,7 +175,7 @@ NDK 22 and 23 are not suggested, because they may report error when link third p
Effect example: Huawei P40, ARM single thread 32.2359ms
-
![](https://gitee.com/darren3d/tnn-resource/raw/master/doc/cn/user/resource/android_face_detector_image.jpg)
+
![](https://github.com/darrenyao87/tnn-models/raw/master/doc/cn/user/resource/image_classify.jpg)
Example: Huawei P40, NPU rom 100.320.010.022 9.04ms
@@ -188,7 +188,7 @@ NDK 22 and 23 are not suggested, because they may report error when link third p
Effect example: Huawei P40, ARM single thread 122.296ms
-
![](https://gitee.com/darren3d/tnn-resource/raw/master/doc/cn/user/resource/android_face_detector_stream.jpg)
+
![](https://github.com/darrenyao87/tnn-models/raw/master/doc/cn/user/resource/android_face_detector_stream.jpg)
Example: Huawei P40, NPU rom 100.320.010.022 28ms
@@ -201,7 +201,7 @@ NDK 22 and 23 are not suggested, because they may report error when link third p
Effect example: Huawei P40, ARM single thread 81.4047ms
-
![](https://gitee.com/darren3d/tnn-resource/raw/master/doc/cn/user/resource/android_image_classify.jpg)
+
![](https://github.com/darrenyao87/tnn-models/raw/master/doc/cn/user/resource/android_image_classify.jpg)
Example: Huawei P40, NPU rom 100.320.010.022 2.48ms
diff --git a/doc/en/user/tech_solution_en.md b/doc/en/user/tech_solution_en.md
index b1be28354..b7d6db0de 100644
--- a/doc/en/user/tech_solution_en.md
+++ b/doc/en/user/tech_solution_en.md
@@ -61,7 +61,7 @@ At present, TNN has been launched in various major businesses, and its following
#### TNN Architecture Diagram:
-
![](https://gitee.com/darren3d/tnn-resource/raw/master/doc/cn/imgs/tnn_architect.jpg)
+
![](https://github.com/darrenyao87/tnn-models/raw/master/doc/en/imgs/tnn_architect.jpg)
* TNN supports TensorFlow, Pytorch, MxNet, Caffe, and other training frameworks through ONNX, leveraging the continuous improvement of the ONNX open-source society.
Currently, TNN supports 55 ONNX operators and will be developed to cover 80 operators shortly, consisting of most of the mainstream CNN operators needed.