with single choice craft_text_detector

app.py

@@ -20,7 +20,7 @@ def detect_with_craft_hw_ocr(image: np.ndarray):
     m=(np.asarray([w,h]))[np.newaxis,np.newaxis,:]
     return annotated, bboxes, is_signature(bboxes/m)
 
-def process(image:np.ndarray, lib:str):
+def process(image:np.ndarray, lib:str='craft_text_detector'):
     if image is None:
         return None,'',''
     annotated, boxes, signed = detect_with_craft_text_detector(image) if lib=='craft_text_detector' else detect_with_craft_hw_ocr( image)
@@ -70,7 +70,8 @@ def is_signature(boxes) -> bool:
 
 gr.Interface(
     fn = process,
-    inputs = [ gr.Image(label="Input"), gr.inputs.Radio(label='Model', choices=["craft_text_detector", "craft_hw_ocr"], default='craft_text_detector') ],
+    # inputs = [ gr.Image(label="Input"), gr.inputs.Radio(label='Model', choices=["craft_text_detector", "craft_hw_ocr"], default='craft_text_detector') ],
+    inputs = [ gr.Image(label="Input") ],
     outputs = [ gr.Image(label="Output"), gr.Label(label="nb of text detections"), gr.Label(label="Has signature") ],
     title="Detect signature in image",
     description="Is the photo or image watermarked by a signature?",

requirements.txt

@@ -1,3 +1,5 @@
+torch>=0.12.1
+torchvision>=0.13.1
 gradio
 Pillow
 opencv-python
@@ -10,3 +12,4 @@ scipy
 psutil
 craft_text_detector
 craft_hw_ocr
+ipython