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| import gradio as gr | |
| from azure.ai.vision.imageanalysis import ImageAnalysisClient | |
| from azure.ai.vision.imageanalysis.models import VisualFeatures | |
| from azure.core.credentials import AzureKeyCredential | |
| def ocr_image_file(image1, end_point, API_Key): | |
| if (end_point == '' or API_Key == ''): | |
| output = "*** Please provide EndPoint URL and API_KEY ***" | |
| else: | |
| try: | |
| endpoint = end_point | |
| key = API_Key | |
| # Create an Image Analysis client | |
| client = ImageAnalysisClient( | |
| endpoint=endpoint, | |
| credential=AzureKeyCredential(key) | |
| ) | |
| # [START read] | |
| # Load image to analyze into a 'bytes' object | |
| with open(image1, "rb") as f: | |
| image_data = f.read() | |
| # Extract text (OCR) from an image stream. This will be a synchronously (blocking) call. | |
| result = client.analyze( | |
| image_data=image_data, | |
| visual_features=[VisualFeatures.READ] | |
| ) | |
| if result.read is not None: | |
| sentence = '' | |
| for line in result.read.blocks[0].lines: | |
| sentence += f" {line.text}" + "\n" | |
| print(f" Line: '{line.text}'") | |
| output = sentence | |
| except : | |
| output = "*** Please check EndPoint URL and API_KEY ***" | |
| return output | |
| title = "Azure Cognitive Services" | |
| description = """ | |
| <img src = "https://nightingalehq.ai/knowledgebase/glossary/what-are-azure-cognitive-services/cognitive-services.jpg" width = 300px> | |
| # Computer Vision : OCR or Optical Character Recognition for text recognition or text extraction. | |
| """ | |
| demo = gr.Interface( ocr_image_file, | |
| [gr.UploadButton("Click to Upload an Image File", file_types=["image"]), gr.Textbox(label="Enter your Endpoint URL", placeholder="URL", lines=1),gr.Textbox(type = "password", label="Enter your API-Key", placeholder="API-Key", lines=1)], | |
| [gr.Textbox(label = "Output")], | |
| title=title, | |
| description=description, | |
| ).launch() |