Merge pull request #69 from MATLAB-Community-Toolboxes-at-INCF/import_fixing

Import fixing

Author: stevevanhooser

Diff for: +deepinterp/+internal/openTensorFlowNetwork.m

@@ -0,0 +1,38 @@
+function net = openTensorFlowNetwork(tensorFlowZipFile, namespaceName)
+% OPENTENSORFLOWNETWORK - open a TensorFlow network zip file
+%
+% NET = OPENTENSORFLOWNETWORK(TENSORFLOWZIPFILE, NAMESPACENAME)
+%
+% Open a network from a saved TensorFlow network zip file.
+%
+% The ZIP file should have a directory with subdirectories "assets",
+% "variables" and files "keras_metadata.pb" and "saved_model.pb".
+%
+% NAMESPACENAME is the namespace to be used to import the network.
+%
+% The namespace is created in the directory:
+%  [DEEP_INTERPOLATION_ROOT filesep 'preTrainedModels' filesep 'TensorFlowNetworks']
+%
+%
+
+tfnet_path = fullfile(deepinterp.toolboxpath,'pretrainedModels','TensorFlowNetworks');
+
+output_files = unzip(tensorFlowZipFile,tfnet_path);
+modelFolder = fileparts(output_files{1});
+net_namespace = namespaceName;
+currDir = pwd;
+
+did_it_fail = false;
+
+try,
+   cd(tfnet_path);
+   net = importNetworkFromTensorFlow(modelFolder,Namespace=namespaceName);
+catch,
+   did_it_fail = true;
+end;
+
+cd(currDir);
+
+if did_it_fail,
+    error(lasterr);
+end;

Diff for: +deepinterp/Net.m

@@ -21,9 +21,10 @@
 			% Create a new deepinterp.Net object according to instructions.
 			% COMMAND can be any of the following:
 			%
-			% 'New'         : create a new network (under development)
-			% 'KerasFile'   : open and import a Keras file
-			% 'Pretrained'  : Open a pretrained model in DeepInterpolation
+			% 'New'            : create a new network (under development)
+			% 'KerasFile'      : open and import a Keras file
+			% 'TensorFlowZip'  : open a TensorFlow zip file
+			% 'Pretrained'     : Open a pretrained model in DeepInterpolation
 			%
 			% The function also accepts additional arguments as name/value pairs:
 			% --------------------------------------------------------------------
@@ -49,8 +50,9 @@
  			% |-------------------------|----------------------------------------|
 			%
 			% Examples:
-			%   n1 = deepinterp.net('Pretrained','model','TP-Ai93-450');
+			%   n1 = deepinterp.Net('Pretrained','model','TP-Ai93-450');
 			%   n2 = deepinterp.Net('KerasFile','file','myKerasFile.H5');
+			%   n3 = deepinterp.Net('TensorFlowZip','file','myTFFile.zip','model','ModelABC');
 			%
 				arguments
 					command (1,:) char {mustBeTextScalar}
@@ -73,6 +75,8 @@
 						error(['NEW option still under development.']);
 					case 'kerasfile',
 						obj.network=deepinterp.internal.importKerasMAE(options.file);
+					case 'tensorflowzip',
+						obj.network=deepinterp.internal.openTensorFlowNetwork(options.file,matlab.lang.makeValidName(options.model));
 					case 'pretrained',
 						[modelfilename, modelparams] = deepinterp.internal.getPretrainedModelFilename(options.model);
 						obj = deepinterp.Net(modelparams.format,'file',modelfilename,...

Diff for: +deepinterp/setup.m

@@ -11,6 +11,7 @@ function setup()
 addpath(tbd);
 addpath(fullfile(tbd, "sampleData"))
 addpath(fullfile(tbd, "pretrainedModels"))
+addpath(fullfile(tbd, "pretrainedModels","TensorFlowNetworks"))
 addpath(fullfile(tbd, "examples"))
 
 

Diff for: examples/other/tiny_ophys_inference_detailed.mlx

@@ -0,0 +1 @@
+

Diff for: examples/tiny_ophys_inference.mlx

@@ -0,0 +1,8 @@
+#The following snippet is executed in Python 3.9 with TensorFlow 2.10. Currently, the import functionality in MATLAB support upto TF 2.10.
+#The command to install TensorFlow 2.10 is:
+#pip install tensorflow==2.10
+
+import tensorflow as tf
+model = tf.keras.models.load_model('2019_09_11_23_32_unet_single_1024_mean_absolute_error_Ai93-0450.h5')
+model.save('TF_2019_09_11_23_32_unet_single_1024_mean_absolute_error_Ai93-0450', save_format='tf')
+

Diff for: interop/.gitkeep

@@ -1,14 +1,14 @@
 [
     {
         "name":"TP-Ai93-450",
-        "filename":"2019_09_11_23_32_unet_single_1024_mean_absolute_error_Ai93-0450.h5",
-        "url":"https://wds-matlab-community-toolboxes.s3.amazonaws.com/DeepInterpolation-MATLAB/Trained_models/ophys/2019_09_11_23_32_unet_single_1024_mean_absolute_error_Ai93-0450.h5",
+        "filename":"",
+        "url":"https://wds-matlab-community-toolboxes.s3.amazonaws.com/DeepInterpolation-MATLAB/Trained_models/ophys/TF_2019_09_11_23_32_unet_single_1024_mean_absolute_error_Ai93-0450.zip",
         "dim":[512,512],
         "pre":30,
         "post":30,
         "omit":1,
         "type":"two-photon",
-        "format": "KerasFile",
+        "format": "TensorFlowZip",
         "license": "https://github.com/MATLAB-Community-Toolboxes-at-INCF/DeepInterpolation-MATLAB/blob/main/LICENSE",
         "parameters":
         {
@@ -27,13 +27,13 @@
     {
         "name":"TP-Ai148",
         "filename":"",
-        "url":"https://wds-matlab-community-toolboxes.s3.amazonaws.com/DeepInterpolation-MATLAB/Trained_models/ophys/2019_09_11_23_32_unet_single_1024_mean_absolute_error_Ai148-0450.h5",
+        "url":"https://wds-matlab-community-toolboxes.s3.amazonaws.com/DeepInterpolation-MATLAB/Trained_models/ophys/2019_09_11_23_32_unet_single_1024_mean_absolute_error_Ai148-0450.zip",
         "dim":[512,512],
         "pre":30,
         "post":30,
         "omit":1,
         "type":"two-photon",
-        "format": "KerasFile",
+        "format": "TensorFlowZip",
         "license": "https://github.com/MATLAB-Community-Toolboxes-at-INCF/DeepInterpolation-MATLAB/blob/main/LICENSE",
         "parameters":
         {