Add Tensorflow demo

tf-mobilenet-image/README.md

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+# Mobilenet Example For WASI-NN with Tensorflow Backend
+
+This package is a high-level Rust bindings for [wasi-nn] example of Mobilenet with Tensorflow backend.
+
+[wasi-nn]: https://github.com/second-state/wasmedge-wasi-nn
+
+## Dependencies
+
+This crate depends on the `wasi-nn` in the `Cargo.toml`:
+
+```toml
+[dependencies]
+wasmedge-wasi-nn = "0.2.1"
+```
+
+## Build
+
+Compile the application to WebAssembly:
+
+```bash
+cd rust/tf-mobilenet && cargo build --target=wasm32-wasi --release
+```
+
+The output WASM file will be at [`rust/tf-mobilenet/target/wasm32-wasi/release/wasmedge-wasinn-example-tf-mobilenet-image.wasm`](wasmedge-wasinn-example-tf-mobilenet-image.wasm).
+To speed up the image processing, we can enable the AOT mode in WasmEdge with:
+
+```bash
+wasmedgec rust/tf-mobilenet/target/wasm32-wasi/release/wasmedge-wasinn-example-tf-mobilenet-image.wasm run.wasm
+```
+
+## Run
+
+### Download fixture
+
+The testing image is located at `./PurpleGallinule.jpg` downloaded from [link](https://raw.githubusercontent.com/second-state/wasm-learning/master/rust/mobilenet_birds_tfhub/PurpleGallinule.jpg).
+
+The `tf` model is located at `./saved_model.pb` downloaded from [link](https://tfhub.dev/google/aiy/vision/classifier/birds_V1/1). Please note that, the model should be saved by tensorflow [SavedModel](https://www.tensorflow.org/guide/saved_model) format with no extra assets and variables.
+
+### Generate Image Tensor
+
+If you want to generate the [raw](birdx224x224x3.rgb) tensor, you can run:
+
+```shell
+cd rust/image-converter/ && cargo run ../../PurpleGallinule.jpg ../../birdX224X224X3.rgb && cd ../..
+```
+
+### Execute
+
+Execute the WASM with the `wasmedge` with Tensorflow supporting:
+
+```bash
+wasmedge --dir .:. wasmedge-wasinn-example-tf-mobilenet-image.wasm saved_model.pb PurpleGallinule.jpg
+```
+
+You will get the output:
+
+```console
+Read graph weights, size in bytes: 3561598
+Loaded graph into wasi-nn with ID: 0
+Created wasi-nn execution context with ID: 0
+Read input tensor, size in bytes: 150528
+Executed graph inference
+   1.) [576](0.8951)Porphyrio martinicus
+   2.) [427](0.0123)Cynanthus latirostris
+   3.) [331](0.0064)Porphyrio poliocephalus
+   4.) [798](0.0039)Porphyrio hochstetteri
+   5.) [743](0.0033)Hemiphaga novaeseelandiae
+```

tf-mobilenet-image/rust/image-converter/Cargo.toml

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+[package]
+name = "image-converter"
+version = "0.1.0"
+edition = "2021"
+
+# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
+
+[dependencies]
+image = { version = "0.23.14", default-features = false, features = ["gif", "jpeg", "ico", "png", "pnm", "tga", "tiff", "webp", "bmp", "hdr", "dxt", "dds", "farbfeld"]  }

tf-mobilenet-image/rust/image-converter/src/main.rs

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+use std::env;
+use std::fs;
+use std::fs::File;
+use std::io::Read;
+
+fn main() {
+    let args: Vec<String> = env::args().collect();
+    let image_name: &str = &args[1];
+    let output_name: &str = &args[2];
+
+    let tensor_data = image_to_tensor(image_name.to_string(), 224, 224);
+    println!(
+        "Read image with {} bytes to write {}",
+        tensor_data.len(),
+        output_name
+    );
+    fs::write(output_name.to_string(), tensor_data).expect("Failed to write tensor")
+}
+
+fn image_to_tensor(path: String, height: u32, width: u32) -> Vec<u8> {
+    let mut file_img = File::open(path).unwrap();
+    let mut img_buf = Vec::new();
+    file_img.read_to_end(&mut img_buf).unwrap();
+    let img = image::load_from_memory(&img_buf).unwrap().to_rgb8();
+    let resized =
+        image::imageops::resize(&img, height, width, ::image::imageops::FilterType::Triangle);
+    let mut flat_img: Vec<f32> = Vec::new();
+    for rgb in resized.pixels() {
+        flat_img.push(rgb[0] as f32 / 255.0);
+        flat_img.push(rgb[1] as f32 / 255.0);
+        flat_img.push(rgb[2] as f32 / 255.0);
+    }
+    let bytes_required = flat_img.len() * 4;
+    let mut u8_f32_arr: Vec<u8> = vec![0; bytes_required];
+
+    for c in 0..3 {
+        for i in 0..(flat_img.len() / 3) {
+            // Read the number as a f32 and break it into u8 bytes
+            let u8_f32: f32 = flat_img[i * 3 + c] as f32;
+            let u8_bytes = u8_f32.to_ne_bytes();
+
+            for j in 0..4 {
+                u8_f32_arr[((i * 3 + c) * 4) + j] = u8_bytes[j];
+            }
+        }
+    }
+    return u8_f32_arr;
+}

tf-mobilenet-image/rust/tf-mobilenet/Cargo.toml

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+[package]
+name = "wasmedge-wasinn-example-tf-mobilenet-image"
+version = "0.19.0"
+authors = ["Second-State"]
+readme = "README.md"
+edition = "2018"
+publish = false
+
+[dependencies]
+image = { version = "0.23.14", default-features = false, features = ["gif", "jpeg", "ico", "png", "pnm", "tga", "tiff", "webp", "bmp", "hdr", "dxt", "dds", "farbfeld"]  }
+wasi-nn = { version = "0.2.1"}
+
+# This crate is built with the wasm32-wasi target, so it's separate
+# from the main Wasmtime build, so use this directive to exclude it
+# from the parent directory's workspace.
+[workspace]