| import os | |
| from PIL import Image, ImageDraw, ImageFont | |
| from .utils import image_label_2_color | |
| def get_flattened_output(docs): | |
| print("Running Flattened Output") | |
| flattened_output = [] | |
| annotation_key = 'output' | |
| for doc in docs: | |
| flattened_output_item = {annotation_key: []} | |
| doc_annotation = doc[annotation_key] | |
| for i, span in enumerate(doc_annotation): | |
| if len(span['words']) > 1: | |
| for span_chunk in span['words']: | |
| flattened_output_item[annotation_key].append( | |
| { | |
| 'label': span['label'], | |
| 'text': span_chunk['text'], | |
| 'words': [span_chunk] | |
| } | |
| ) | |
| else: | |
| flattened_output_item[annotation_key].append(span) | |
| flattened_output.append(flattened_output_item) | |
| return flattened_output | |
| def annotate_image(image_path, annotation_object): | |
| print("Annotating Images") | |
| img = None | |
| image = Image.open(image_path).convert('RGBA') | |
| tmp = image.copy() | |
| label2color = image_label_2_color(annotation_object) | |
| overlay = Image.new('RGBA', tmp.size, (0, 0, 0)+(0,)) | |
| draw = ImageDraw.Draw(overlay) | |
| font = ImageFont.load_default() | |
| predictions = [span['label'] for span in annotation_object['output']] | |
| boxes = [span['words'][0]['box'] for span in annotation_object['output']] | |
| for prediction, box in zip(predictions, boxes): | |
| draw.rectangle(box, outline=label2color[prediction], | |
| width=3, fill=label2color[prediction]+(int(255*0.33),)) | |
| draw.text((box[0] + 10, box[1] - 10), text=prediction, | |
| fill=label2color[prediction], font=font) | |
| img = Image.alpha_composite(tmp, overlay) | |
| img = img.convert("RGB") | |
| image_name = os.path.basename(image_path) | |
| image_name = image_name[:image_name.find('.')] | |
| output_folder = 'static/temp/inferenced/' | |
| os.makedirs(output_folder, exist_ok=True) | |
| img.save(os.path.join(output_folder, f'{image_name}_inference.jpg')) | |