Upload 3 files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* 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
+arabic_signlanguage_characters_model.task filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,37 @@
+import cv2
+import mediapipe as mp
+from mediapipe.tasks import python
+from mediapipe.tasks.python import vision
+import gradio as gr
+import os
+
+def recognize_gesture(image):
+    # Load the gesture recognition model
+    model_path = os.path.abspath("arabic_signlanguage_characters_model.task")
+    recognizer = vision.GestureRecognizer.create_from_model_path(model_path)
+
+    # Convert image to MediaPipe format
+    if isinstance(image, gr.Image):  # Check if image is from Gradio
+        image = image.to_ndarray(format="bgr")  # Convert to a NumPy array in BGR format
+
+    # Convert image to MediaPipe format
+    image = mp.Image(image_format=mp.ImageFormat.SRGB, data=image)
+
+    # Perform gesture recognition
+    recognition_result = recognizer.recognize(image)
+
+    # Extract the top gesture
+    top_gesture = recognition_result.gestures[0][0]
+
+    # Return the gesture label and score
+    return f"Gesture recognized: {top_gesture.category_name} ({top_gesture.score:.2f})"
+
+iface = gr.Interface(
+    fn=recognize_gesture,
+    inputs=["image"],  # Input type: image
+    outputs="text",  # Output type: text
+    title="Arabic Sign Language Character Recognition",
+    description="Upload an image to recognize the gesture",
+)
+
+iface.launch(share=True)  # Launch the interface in a web browser

arabic_signlanguage_characters_model.task

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bd86421edd79714e6091d60bc2c96117ea8ad09521834a6971fd46d107398053
+size 8473894

requirements.txt

@@ -0,0 +1,2 @@
+mediapipe
+os