Test

.gitattributes

@@ -32,4 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.xz filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text

.gitignore

@@ -0,0 +1 @@
+.env

.gradio/flagged/dataset1.csv

@@ -0,0 +1,2 @@
+img,output,timestamp
+.gradio\flagged\img\a84bae4ef9dfb0970622\download.jpg,,2025-05-20 22:55:10.594148

app.py

@@ -0,0 +1,21 @@
+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+
+model = tf.keras.models.load_model("best_alphabet_model.h5")
+
+def process(img):
+    img = img.resize((224,224))
+    img = np.array(img) / 255.0
+    return np.expand_dims(img, axis=1)
+
+def predict(img):
+    # img = process(img)
+    # pred = model.predict(img)
+    # class_idx = np.argmax(pred)
+    # return f"Class : {class_idx} (confidence : {pred[0][class_idx]:.2f})"
+    return "Heheha"
+
+interface = gr.Interface(fn=predict, inputs=gr.Image(type="pil"),outputs="text")
+interface.launch()

best_alphabet_model.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aa682d7138e5e6ba95b28c57eb496120904431e81472c24e0cb3c20bb77708ea
+size 28783456

requirements.txt

@@ -0,0 +1,4 @@
+gradio
+tensorflow
+Pillow
+numpy