Upload text_detection/app.py with huggingface_hub

text_detection/app.py

@@ -0,0 +1,35 @@
+import os
+
+import gradio as gr
+from imgutils.detect import detection_visualize
+
+from detect import _ALL_MODELS, _DEFAULT_MODEL, detect_text
+
+
+def _gr_detect_text(image, model: str, threshold: float):
+    return detection_visualize(image, detect_text(image, model, threshold))
+
+
+if __name__ == '__main__':
+    with gr.Blocks() as demo:
+        with gr.Row():
+            with gr.Column():
+                gr_face_input_image = gr.Image(type='pil', label='Original Image')
+                gr_face_model = gr.Dropdown(_ALL_MODELS, value=_DEFAULT_MODEL, label='Model')
+                with gr.Row():
+                    gr_face_score_threshold = gr.Slider(0.0, 1.0, 0.05, label='Score Threshold')
+
+                gr_face_submit = gr.Button(value='Submit', variant='primary')
+
+            with gr.Column():
+                gr_face_output_image = gr.Image(type='pil', label="Labeled")
+
+            gr_face_submit.click(
+                _gr_detect_text,
+                inputs=[
+                    gr_face_input_image, gr_face_model, gr_face_score_threshold,
+                ],
+                outputs=[gr_face_output_image],
+            )
+
+    demo.queue(os.cpu_count()).launch()