Update app.py

app.py

@@ -21,112 +21,62 @@ def draw_boxes(image, bounds, color='yellow', width=2):
         draw.line([*p0, *p1, *p2, *p3, *p0], fill=color, width=width)
     return image
 
-def inference(img, lang):
+def inference(img_path, lang):
     reader = easyocr.Reader(lang)
-    bounds = reader.readtext(img.name)
-    im = PIL.Image.open(img.name)
+    bounds = reader.readtext(img_path)
+    im = PIL.Image.open(img_path)
     draw_boxes(im, bounds)
     im.save('result.jpg')
-    return ['result.jpg', pd.DataFrame(bounds).iloc[: , 1:]]
+
+    # return dataframe with only text + confidence
+    df = pd.DataFrame(bounds)[[1, 2]]
+    df.columns = ["text", "confidence"]
+
+    return 'result.jpg', df
 
 title = 'EasyOCR'
-description = 'Gradio demo for EasyOCR. EasyOCR demo supports 80+ languages.To use it, simply upload your image and choose a language from the dropdown menu, or click one of the examples to load them. Read more at the links below.'
-article = "<p style='text-align: center'><a href='https://www.jaided.ai/easyocr/'>Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.</a> | <a href='https://github.com/JaidedAI/EasyOCR'>Github Repo</a></p>"
-examples = [['english.png',['en']],['thai.jpg',['th']],['french.jpg',['fr', 'en']],['chinese.jpg',['ch_sim', 'en']],['japanese.jpg',['ja', 'en']],['korean.png',['ko', 'en']],['Hindi.jpeg',['hi', 'en']]]
+description = """
+EasyOCR demo supports 80+ languages.  
+Upload an image and choose a language to extract text.
+"""
+article = "<p style='text-align: center'><a href='https://www.jaided.ai/easyocr/'>EasyOCR Website</a> | <a href='https://github.com/JaidedAI/EasyOCR'>GitHub Repo</a></p>"
+
+examples = [
+    ['english.png', ['en']],
+    ['thai.jpg', ['th']],
+    ['french.jpg', ['fr', 'en']],
+    ['chinese.jpg', ['ch_sim', 'en']],
+    ['japanese.jpg', ['ja', 'en']],
+    ['korean.png', ['ko', 'en']],
+    ['Hindi.jpeg', ['hi', 'en']]
+]
+
 css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
+
 choices = [
-    "abq",
-    "ady",
-    "af",
-    "ang",
-    "ar",
-    "as",
-    "ava",
-    "az",
-    "be",
-    "bg",
-    "bh",
-    "bho",
-    "bn",
-    "bs",
-    "ch_sim",
-    "ch_tra",
-    "che",
-    "cs",
-    "cy",
-    "da",
-    "dar",
-    "de",
-    "en",
-    "es",
-    "et",
-    "fa",
-    "fr",
-    "ga",
-    "gom",
-    "hi",
-    "hr",
-    "hu",
-    "id",
-    "inh",
-    "is",
-    "it",
-    "ja",
-    "kbd",
-    "kn",
-    "ko",
-    "ku",
-    "la",
-    "lbe",
-    "lez",
-    "lt",
-    "lv",
-    "mah",
-    "mai",
-    "mi",
-    "mn",
-    "mr",
-    "ms",
-    "mt",
-    "ne",
-    "new",
-    "nl",
-    "no",
-    "oc",
-    "pi",
-    "pl",
-    "pt",
-    "ro",
-    "ru",
-    "rs_cyrillic",
-    "rs_latin",
-    "sck",
-    "sk",
-    "sl",
-    "sq",
-    "sv",
-    "sw",
-    "ta",
-    "tab",
-    "te",
-    "th",
-    "tjk",
-    "tl",
-    "tr",
-    "ug",
-    "uk",
-    "ur",
-    "uz",
-    "vi"
+    "abq","ady","af","ang","ar","as","ava","az","be","bg","bh","bho","bn","bs","ch_sim","ch_tra","che",
+    "cs","cy","da","dar","de","en","es","et","fa","fr","ga","gom","hi","hr","hu","id","inh","is","it",
+    "ja","kbd","kn","ko","ku","la","lbe","lez","lt","lv","mah","mai","mi","mn","mr","ms","mt","ne",
+    "new","nl","no","oc","pi","pl","pt","ro","ru","rs_cyrillic","rs_latin","sck","sk","sl","sq","sv",
+    "sw","ta","tab","te","th","tjk","tl","tr","ug","uk","ur","uz","vi"
 ]
-gr.Interface(
-    inference,
-    [gr.inputs.Image(type='file', label='Input'),gr.inputs.CheckboxGroup(choices, type="value", default=['en'], label='language')],
-    [gr.outputs.Image(type='file', label='Output'), gr.outputs.Dataframe(headers=['text', 'confidence'])],
+
+demo = gr.Interface(
+    fn=inference,
+    inputs=[
+        gr.Image(type="filepath", label="Input Image"),
+        gr.CheckboxGroup(choices=choices, value=["en"], label="Language")
+    ],
+    outputs=[
+        gr.Image(label="Output"),
+        gr.Dataframe(label="Detected Text")
+    ],
     title=title,
     description=description,
     article=article,
     examples=examples,
     css=css,
     enable_queue=True
-    ).launch(debug=True)
+)
+
+demo.launch(debug=True)