Create app.py

app.py

@@ -0,0 +1,69 @@
+import gradio as gr
+from transformers import pipeline
+import torch 
+from PIL import Image
+
+# Load models
+pipe = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")  
+translator = pipeline(task="translation", model="facebook/nllb-200-distilled-600M", torch_dtype=torch.bfloat16)
+
+def process_image(image, shouldConvert=False):
+    if shouldConvert:
+        new_img = Image.new('RGB', size=(image.width, image.height), color=(255, 255, 255))
+        new_img.paste(image, (0, 0), mask=image)
+        image = new_img
+    return image
+
+def parse_input(image, sketchpad, state):
+    current_tab_index = state["tab_index"]
+    new_image = None
+    
+    # Upload
+    if current_tab_index == 0:
+        if image is not None:
+            new_image = process_image(image)
+
+    # Sketch
+    elif current_tab_index == 1:
+        #print(sketchpad)
+        if sketchpad and sketchpad["composite"]:
+            new_image = process_image(sketchpad["composite"], True)
+    
+    Eng_txt = pipe(new_image)
+    to_Ar_txt = str(Eng_txt[0]['generated_text'])
+    text_translated = translator(to_Ar_txt, src_lang="eng_Latn", tgt_lang="arz_Arab")
+    return text_translated[0]['translation_text']
+
+
+def tabs_select(e: gr.SelectData, _state):
+    _state["tab_index"] = e.index
+
+with gr.Blocks() as iface:
+    gr.HTML("""<p align="center"><img src="https://cdn-icons-png.flaticon.com/512/5853/5853758.png" style="height: 60px"/><p>""")
+    gr.HTML("""<center><font size=8>Image Captioning Demo</center>""")
+    gr.HTML("""<center><font size=3>In this space you can input either an image or draw a sketch of objects to recieve an Arabic caption.</center>""")
+
+    state = gr.State({"tab_index": 0})
+    
+    with gr.Row():
+        with gr.Column():
+            with gr.Tabs() as input_tabs:
+                with gr.Tab("Upload"):
+                    input_image = gr.Image(type="pil", label="Upload")
+                with gr.Tab("Sketch"):
+                    input_sketchpad = gr.Sketchpad(type="pil", label="Sketch", layers=False)
+            input_tabs.select(fn=tabs_select, inputs=[state])
+            with gr.Row():
+                with gr.Column():
+                    clear_btn = gr.ClearButton(
+                        [input_image, input_sketchpad])
+                with gr.Column():
+                    submit_btn = gr.Button("Submit", variant="primary")
+        submit_btn.click(
+            fn=parse_input,
+            inputs=[input_image, input_sketchpad, state],
+            outputs= gr.Textbox(label = "Result")) 
+           
+# Launch the interface
+if __name__ == "__main__":
+    iface.launch()