将一个 VNCoreMLFeatureValueObservation 结果(3D Double Array)转换为多个 UIImage
Convert a VNCoreMLFeatureValueObservation result (3D Double Array) into multiple UIImages
我有一个 coreml 模型,在 运行 之后,returns 一个 VNCoreMLFeatureValueObservation 对象带有 1 "MultiArray : Double 10 x IMG_SIZE x IMG_SIZE array"
我如何将其转换为 10 个 UIImage,每个具有 IMG_SIZE x IMG_SIZE 尺寸,并且它们的值为灰度?
在四处窥探之后,我发现我必须添加这些辅助函数:
https://github.com/hollance/CoreMLHelpers 到我的 Xcode 项目。
从 MultiArray Initialization 问题:
然后我拼凑了这个解决方案:
let request = VNCoreMLRequest(model: model) { (request, error) in
guard let results = request.results as? [VNCoreMLFeatureValueObservation] else {
fatalError("Model failed to process image")
}
let obs : VNCoreMLFeatureValueObservation = (results.first)!
let m: MLMultiArray = obs.featureValue.multiArrayValue!
var mArrays = [MLMultiArray]()
for i in 0..<10 {
let start = i*(IMG_SIZE*IMG_SIZE)
guard let tmp : MLMultiArray = try? MLMultiArray(shape:[768,768], dataType:MLMultiArrayDataType.double) else {
fatalError("Unexpected runtime error. MLMultiArray")
}
for n in 0..<(IMG_SIZE*IMG_SIZE) {
tmp[n] = m[start+n]
}
mArrays.append(tmp)
}
self.imagePred0.image = mArrays[0].image(offset: 0, scale: 255)!
self.imagePred1.image = mArrays[1].image(offset: 0, scale: 255)!
self.imagePred2.image = mArrays[2].image(offset: 0, scale: 255)!
self.imagePred3.image = mArrays[3].image(offset: 0, scale: 255)!
self.imagePred4.image = mArrays[4].image(offset: 0, scale: 255)!
self.imagePred5.image = mArrays[5].image(offset: 0, scale: 255)!
self.imagePred6.image = mArrays[6].image(offset: 0, scale: 255)!
self.imagePred7.image = mArrays[7].image(offset: 0, scale: 255)!
self.imagePred8.image = mArrays[8].image(offset: 0, scale: 255)!
self.imagePred9.image = mArrays[9].image(offset: 0, scale: 255)!
}
希望有更简洁的方法,但目前有效
我有一个 coreml 模型,在 运行 之后,returns 一个 VNCoreMLFeatureValueObservation 对象带有 1 "MultiArray : Double 10 x IMG_SIZE x IMG_SIZE array"
我如何将其转换为 10 个 UIImage,每个具有 IMG_SIZE x IMG_SIZE 尺寸,并且它们的值为灰度?
在四处窥探之后,我发现我必须添加这些辅助函数:
https://github.com/hollance/CoreMLHelpers 到我的 Xcode 项目。 从 MultiArray Initialization 问题:
然后我拼凑了这个解决方案:
let request = VNCoreMLRequest(model: model) { (request, error) in
guard let results = request.results as? [VNCoreMLFeatureValueObservation] else {
fatalError("Model failed to process image")
}
let obs : VNCoreMLFeatureValueObservation = (results.first)!
let m: MLMultiArray = obs.featureValue.multiArrayValue!
var mArrays = [MLMultiArray]()
for i in 0..<10 {
let start = i*(IMG_SIZE*IMG_SIZE)
guard let tmp : MLMultiArray = try? MLMultiArray(shape:[768,768], dataType:MLMultiArrayDataType.double) else {
fatalError("Unexpected runtime error. MLMultiArray")
}
for n in 0..<(IMG_SIZE*IMG_SIZE) {
tmp[n] = m[start+n]
}
mArrays.append(tmp)
}
self.imagePred0.image = mArrays[0].image(offset: 0, scale: 255)!
self.imagePred1.image = mArrays[1].image(offset: 0, scale: 255)!
self.imagePred2.image = mArrays[2].image(offset: 0, scale: 255)!
self.imagePred3.image = mArrays[3].image(offset: 0, scale: 255)!
self.imagePred4.image = mArrays[4].image(offset: 0, scale: 255)!
self.imagePred5.image = mArrays[5].image(offset: 0, scale: 255)!
self.imagePred6.image = mArrays[6].image(offset: 0, scale: 255)!
self.imagePred7.image = mArrays[7].image(offset: 0, scale: 255)!
self.imagePred8.image = mArrays[8].image(offset: 0, scale: 255)!
self.imagePred9.image = mArrays[9].image(offset: 0, scale: 255)!
}
希望有更简洁的方法,但目前有效