validating single image predict for fashion_mnist - kamangir/bolt#692

abcli/fashion_mnist.sh

@@ -10,8 +10,8 @@ function abcli_fashion_mnist() {
     if [ $task == "help" ] ; then
         abcli_help_line "$abcli_cli_name fashion_mnist ingest" \
             "ingest fashion_mnist data."
-        abcli_help_line "$abcli_cli_name fashion_mnist predict object_1 [name_1] [object]" \
-            "run fashion_mnist saved/object model name_1 predict on object_1."
+        abcli_help_line "$abcli_cli_name fashion_mnist predict data_1 [name_1] [data=filename/*object/url,model=object/*saved]" \
+            "run fashion_mnist saved/object model name_1 predict on filename/object/url data_1."
         abcli_help_line "$abcli_cli_name fashion_mnist save [name_1] [object_1] [force]" \
             "[force] save fashion_mnist [in object_1] [as name_1]."
         abcli_help_line "$abcli_cli_name fashion_mnist train [validate]" \
@@ -35,8 +35,12 @@ function abcli_fashion_mnist() {
     fi
 
     if [ "$task" == "predict" ] ; then
-        local data_object=$(abcli_clarify_object "$2" $abcli_object_name)
+        # Args
+        #  $2: data_1: data for prediction
+        #  $3: name_1: model name
+        #  $4: options: data=filename/*object/url,model=object/*saved
 
+        local data_object=$(abcli_clarify_object "$2" $abcli_object_name)
         if [ "$(abcli_keyword_is $data_object validate)" == true ] ; then
             local output_object=$abcli_object_name
 
@@ -47,8 +51,7 @@ function abcli_fashion_mnist() {
             abcli_select $output_object ~trail
         fi
 
-        abcli_huggingface predict \
-            image-classifier \
+        abcli_image_classifier predict \
             $data_object \
             $(abcli_clarify_arg "$3" fashion-mnist) \
             ${@:4}

abcli/image_classifier.sh

@@ -12,8 +12,8 @@ function abcli_image_classifier() {
             "describe model object_1."
         abcli_help_line "$abcli_cli_name image_classifier install" \
             "install image_classifier."
-        abcli_help_line "$abcli_cli_name image_classifier predict object_1 [name_1] [object]" \
-            "run image_classifier saved/object model name_1 predict on object_1."
+        abcli_help_line "$abcli_cli_name image_classifier predict data_1 [name_1] [data=filename/*object/url,model=object/*saved]" \
+            "run fashion_mnist saved/object model name_1 predict on filename/object/url data_1."
         abcli_help_line "$abcli_cli_name image_classifier save [name_1] [object_1] [force]" \
             "[force] save image_classifier [in object_1] [as name_1]."
         abcli_help_line "$abcli_cli_name image_classifier train object_1" \
@@ -48,15 +48,6 @@ function abcli_image_classifier() {
         return
     fi
 
-    if [ "$task" == "predict" ] ; then
-        abcli_huggingface predict \
-            image-classifier \
-            $2 \
-            $(abcli_clarify_arg "$3" image-classifier) \
-            ${@:4}
-        return
-    fi
-
     if [ "$task" == "save" ] ; then
         abcli_huggingface save \
             image-classifier \
@@ -69,36 +60,48 @@ function abcli_image_classifier() {
 }
 
 function abcli_image_classifier_predict() {
-    local model_object=$(abcli_clarify_object "$1")
-    local data_object=$(abcli_clarify_object "$2")
+    # Args
+    #  $1: data_1: data for prediction
+    #  $2: name_1: model name
+    #  $3: options: data=filename/*object/url,model=object/*saved
+
+    local data_object=$(abcli_clarify_object "$1")
+
+    local model_path=$(abcli_huggingface get_model_path image-classifier "$2" "$3")
+
+    local options=$3
+    local model_source=$(abcli_option "$options" "model" saved)
 
-    abcli_download object $model_object
     abcli_download object $data_object
+    if [ "$model_source" == "object" ] ; then
+        local model_object=TBD 
+        abcli_download object $model_object
+    fi
 
-    abcli_log "image_classifier($model_object).predict($data_object)"
+    abcli_log "image_classifier($model_path).predict($data_object)"
 
     if [ ! -f "$abcli_object_root/$data_object/test_images.pyndarray" ] ; then
         python3 -m image_classifier \
             preprocess \
             --infer_annotation 0 \
-            --model_path $abcli_object_root/$model_object \
+            --model_path $model_path \
             --objects $abcli_object_root/$data_object \
             --output_path $abcli_object_root/$data_object \
             --purpose predict \
             ${@:3}
     fi
 
-    cp -v ../$data_object/*.pyndarray .
-    cp -v ../$model_object/image_classifier/model/class_names.json .
+    cp -v $abcli_object_root/$data_object/*.pyndarray .
+    cp -v $model_path/image_classifier/model/class_names.json .
 
     python3 -m image_classifier \
         predict \
         --data_path $abcli_object_root/$data_object \
-        --model_path $abcli_object_root/$model_object \
+        --model_path $model_path \
         --output_path $abcli_object_path \
         ${@:4}
 
-        abcli_tag set . image_classifier,predict
+    abcli_tag set . image_classifier,predict
 }
 
 function abcli_image_classifier_train() {

image_classifier/__init__.py

@@ -1,5 +1,5 @@
 name = "image_classifier"
 
-version = "1.1.131"
+version = "1.1.134"
 
 description = "fashion-mnist + hugging-face + awesome-bash-cli"