tensorflowjs 加载重新训练的 coco-ssd 模型 - 无法在浏览器中运行
2019-02-09
2170
我使用 Python models/research/object-detection API 用我自己的数据集重新训练了 coco-ssd。 我已经保存了模型,并且该模型在 ipython 笔记本中运行。 我使用 tfjs_converter 对其进行了转换 tensorflowjs_converter --input_format=tf_saved_model --output_format=tensorflowjs --output_node_names='detection_boxes,detection_classes,detection_scores,num_detections' --saved_model_tags=serve ./saved_model ./web_model
测试 1;我的代码
image.src = imageURL;
var img;
const runButton = document.getElementById('run');
runButton.onclick = async () => {
console.log('model start');
const model = await modelPromise;
console.log('model loaded');
const zeros = tf.zeros([1, 224, 224, 3]);
const batched = tf.tidy(() => {
if (!(image instanceof tf.Tensor)) {
img = tf.fromPixels(image);
}
// Reshape to a single-element batch so we can pass it to executeAsync.
return img.expandDims(0);
});
console.log('model loaded - now predict .. start');
const result = await model.executeAsync(batched) ;
console.log('model loaded - now predict - ready'); // Error seen
batched.dispose();
tf.dispose(result);
model loaded - now predict .. start ( i tried chaning the model to Coco-ssd model same error)
tensor_array.ts:116 Uncaught (in promise) Error: TensorArray : Could not write to TensorArray index 0,
because the value dtype is int32, but TensorArray dtype is float32.
at e.write (tensor_array.ts:116)
at tensor_array.ts:162
at Array.forEach (<anonymous>)
at e.writeMany (tensor_array.ts:162)
at e.scatter (tensor_array.ts:252)
at control_executor.ts:127
at callbacks.ts:17
at Object.next (callbacks.ts:17)
at callbacks.ts:17```
Test 2; ---- using tfjs-model/coco-ssd/demo ----------------------------------
did yarn , yarn watch
I replaced the coo-ssd model which works correctly, with my re-trained model (only switched the models)
//BASE_PATH = "https://storage.googleapis.com/tfjs-models/savedmodel/";
BASE_PATH = "http://localhost:1234/web_model/";
//this.modelPath = "" + BASE_PATH + this.getPrefix(e) +
"/tensorflowjs_model.pb", this.weightPath = "" + BASE_PATH +
this.getPrefix(e) + "/weights_manifest.json";
``this.modelPath = "" + BASE_PATH + "tensorflowjs_model.pb",
this.weightPath = "" +BASE_PATH + "weights_manifest.json";``
I get an error
io_utils.ts:116 Uncaught (in promise) RangeError: byte length of float32Array should be a multiple of 4
at new Float32Array (<anonymous>)
at o (io_utils.ts:116)
at Object.decodeWeights (io_utils.ts:79)
at e.<anonymous> (frozen_model.ts:109)
at exports_regularizers.ts:47
at Object.next (exports_regularizers.ts:47)
at s (exports_regularizers.ts:47)```
model loaded - now predict .. start ( i tried chaning the model to Coco-ssd model same error)
```tensor_array.ts:116 Uncaught (in promise) Error: TensorArray : Could not write to TensorArray index 0,
because the value dtype is int32, but TensorArray dtype is float32.
at e.write (tensor_array.ts:116)
at tensor_array.ts:162
at Array.forEach (<anonymous>)
at e.writeMany (tensor_array.ts:162)
at e.scatter (tensor_array.ts:252)
at control_executor.ts:127```
at callbacks.ts:17
at Object.next (callbacks.ts:17)
at callbacks.ts:17
2个回答
错误与您用于预测的张量图像有关。
tf.fromPixel 创建一个张量图像,其值范围为 0 到 255,dtype 为 int。由于您的模型正在等待 dtype 为 float32 的张量,您可以将类型转换为 float,也可以将张量值更改为介于 0 和 1 之间
- 转换为 float32
img = tf.fromPixels(image).cast('float32')
- 移动值以适应 0 和 1 之间
img = tf.fromPixels(image).div(256)
edkeveked
2019-02-12
尝试这些转换参数。他们在与Mobilenet_v1进行重新培训后为我工作 output_node_names =“后处理器/explages_1,后处理器/slice”
https://github.com/tensorflow/tfjs-models/tree/master/coco-ssd
Dhrumil
2019-03-01