feat: closes #22

views/models/edit.html

@@ -289,7 +289,12 @@
 {{ end }}
 
 {{ define "run-model-card" }}
-    <form hx-headers='{"REQUEST-TYPE": "html"}' enctype="multipart/form-data" hx-post="/models/run">
+    <form hx-headers='{"REQUEST-TYPE": "html"}' enctype="multipart/form-data" hx-post="/models/run" hx-swap="outerHTML">
+        {{ if .Result }}
+            <div>
+                Img Class: {{.Result}}
+            </div>
+        {{ end }}
         <input type="hidden" name="id" value={{.Model.Id}} />
         <fieldset class="file-upload" >
             <label for="file">Image</label>

views/py/python_model_template.py

@@ -11,8 +11,9 @@ dataset = keras.utils.image_dataset_from_directory(
   "{{ .DataDir }}",
   color_mode="rgb",
   validation_split=0.2,
-  label_mode='int',
+  label_mode='categorical',
   seed=seed,
+  shuffle=True,
   subset="training",
   image_size=({{ .Size }}),
   batch_size=batch_size)
@@ -21,8 +22,9 @@ dataset_validation = keras.utils.image_dataset_from_directory(
   "{{ .DataDir }}",
   color_mode="rgb",
   validation_split=0.2,
-  label_mode='int',
+  label_mode='categorical',
   seed=seed,
+  shuffle=True,
   subset="validation",
   image_size=({{ .Size }}),
   batch_size=batch_size)
@@ -42,11 +44,11 @@ model = keras.Sequential([
 ])
 
 model.compile(
-    loss=losses.SparseCategoricalCrossentropy(),
+    loss=losses.CategoricalCrossentropy(),
     optimizer=tf.keras.optimizers.Adam(),
     metrics=['accuracy'])
 
-his = model.fit(dataset, validation_data= dataset_validation, epochs=70)
+his = model.fit(dataset, validation_data= dataset_validation, epochs=50)
 
 acc = his.history["accuracy"]