app pronto

.gitignore

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+teste.ipynb
+.ipynb_checkpoints/teste-checkpoint.ipynb

app.py

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+import gradio as gr
+from fastai.vision.all import *
+import requests
+
+# learn = load_learner('bedroom_or_kitchen.pkl', 'rb')
+
+# categories = ("Bedroom", "Kitchen")
+
+# def classify_image(img):
+#     pred, idx, probs = learn.predict(img)
+#     return dict(zip(categories, map(float, probs)))
+
+def get_ocr_prediction(img):
+    url = 'https://app.nanonets.com/api/v2/OCR/Model/50440c27-8fb2-4644-a156-75ce1a3c7586/LabelFile/?async=false'
+
+    data = {'file': open(img, 'rb')}
+
+    response = requests.post(url, auth=requests.auth.HTTPBasicAuth('Dpe3_Fz3XZoYtzMN8nUtsmcDh5t4QYnG', ''), files=data)
+
+    buyer_name = [a for a in response.json()["result"][0]["prediction"] if a["label"]=="buyer_name"][0]["ocr_text"]
+    buyer_address = [a for a in response.json()["result"][0]["prediction"] if a["label"]=="buyer_address"][0]["ocr_text"]
+    text = buyer_name+";"+buyer_address
+    
+    return text
+
+
+image = gr.inputs.Image(shape=(192, 192))
+text = gr.outputs.Textbox()
+
+examples = ['teste.jpg']
+
+intf = gr.Interface(fn=get_ocr_prediction, inputs=image, outputs=text, examples=examples)
+
+intf.launch()