Update app.py

app.py

@@ -1,35 +1,162 @@
-import os
-import gradio as gr
-import omegaconf
-import torch
-from vietocr.model.transformerocr import VietOCR
-from vietocr.model.vocab import Vocab
-from vietocr.translate import translate, process_input
-
-examples_data = os.listdir('examples')
-examples_data = [os.path.join('examples', line.split('\t')[0]) for line in examples_data]
-
-config = omegaconf.OmegaConf.load("vgg-seq2seq.yaml")
-config = omegaconf.OmegaConf.to_container(config, resolve=True)
-
-vocab = Vocab(config['vocab'])
-model = VietOCR(len(vocab),
-        config['backbone'],
-        config['cnn'], 
-        config['transformer'],
-        config['seq_modeling'])
-model.load_state_dict(torch.load('train_old.pth', map_location=torch.device('cpu')))
-
-def predict(inp):
-    img = process_input(inp, config['dataset']['image_height'], 
-                    config['dataset']['image_min_width'], config['dataset']['image_max_width'])
-    out = translate(img, model)[0].tolist()
-    out = vocab.decode(out)
-    return out
-
-gr.Interface(fn=predict,
-             title='Vietnamese Handwriting Recognition',
-             inputs=gr.Image(type='pil'),
-             outputs=gr.Text(),
-             examples=examples_data,
-).launch()
+import pandas as pd
+import PIL
+from PIL import Image
+from PIL import ImageDraw
+import gradio as gr
+import torch
+import easyocr
+import omegaconf
+
+from vietocr.model.transformerocr import VietOCR
+from vietocr.model.vocab import Vocab
+from vietocr.translate import translate, process_input
+
+config = omegaconf.OmegaConf.load("vgg-seq2seq.yaml")
+config = omegaconf.OmegaConf.to_container(config, resolve=True)
+
+vocab = Vocab(config['vocab'])
+model = VietOCR(len(vocab),
+        config['backbone'],
+        config['cnn'], 
+        config['transformer'],
+        config['seq_modeling'])
+model.load_state_dict(torch.load('train_old.pth', map_location=torch.device('cpu')))
+
+torch.hub.download_url_to_file('https://github.com/JaidedAI/EasyOCR/raw/master/examples/english.png', 'english.png')
+torch.hub.download_url_to_file('https://github.com/JaidedAI/EasyOCR/raw/master/examples/thai.jpg', 'thai.jpg')
+torch.hub.download_url_to_file('https://github.com/JaidedAI/EasyOCR/raw/master/examples/french.jpg', 'french.jpg')
+torch.hub.download_url_to_file('https://github.com/JaidedAI/EasyOCR/raw/master/examples/chinese.jpg', 'chinese.jpg')
+torch.hub.download_url_to_file('https://github.com/JaidedAI/EasyOCR/raw/master/examples/japanese.jpg', 'japanese.jpg')
+torch.hub.download_url_to_file('https://github.com/JaidedAI/EasyOCR/raw/master/examples/korean.png', 'korean.png')
+torch.hub.download_url_to_file('https://i.imgur.com/mwQFd7G.jpeg', 'Hindi.jpeg')
+
+def draw_boxes(image, bounds, color='yellow', width=2):
+    draw = ImageDraw.Draw(image)
+    for bound in bounds:
+        p0, p1, p2, p3 = bound[0]
+        draw.line([*p0, *p1, *p2, *p3, *p0], fill=color, width=width)
+    return image
+
+def inference(img, lang):
+    reader = easyocr.Reader(lang)
+    bounds = reader.readtext(img.name)
+    new_bounds=[]
+    for (bbox, text, prob) in bounds:
+        y0 = bbox[0].min()
+        y1 = bbox[0].max()
+        x0 = bbox[1].min()
+        x1 = bbox[1].max()
+        
+        # crop the region of interest (ROI)
+        img = img[y0:y1, x0:x1]
+        img = process_input(img, config['dataset']['image_height'], 
+                    config['dataset']['image_min_width'], config['dataset']['image_max_width'])
+        out = translate(img, model)[0].tolist()
+        out = vocab.decode(out)
+        new_bounds.append(bbox, out, prob)
+    im = PIL.Image.open(img.name)
+    draw_boxes(im, bounds)
+    im.save('result.jpg')
+    return ['result.jpg', pd.DataFrame(new_bounds).iloc[: , 1:]]
+
+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']]]
+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"
+]
+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'])],
+    title=title,
+    description=description,
+    article=article,
+    examples=examples,
+    css=css,
+    enable_queue=True
+    ).launch(debug=True)