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| import gradio as gr | |
| from PIL import Image,ImageDraw, ImageFont, ImageOps | |
| import sys | |
| import torch | |
| from util import Detection, load_font | |
| import os | |
| if os.environ.get('FACE_MODEL') is not None: | |
| face_model = os.environ.get('FACE_MODEL') | |
| age_model = os.environ.get('AGE_MODEL') | |
| torch.hub.download_url_to_file(face_model, 'face_model.pt') | |
| torch.hub.download_url_to_file(age_model, 'age_model.pt') | |
| sys.path.append("./") | |
| sys.path.append("./yolov5") | |
| from yolov5.detect import predict, load_yolo_model | |
| # Load Models | |
| model, stride, names, pt, jit, onnx, engine = load_yolo_model("face_model.pt", imgsz=[320,320]) | |
| age_model_ts = torch.jit.load("age_model.pt") | |
| text_box_height = 22 | |
| roboto_font = load_font(height_px=text_box_height-2) | |
| def run_yolo(img0, with_random_augs): | |
| img0 = ImageOps.contain(img0, (640,640)) | |
| img0 = ImageOps.exif_transpose(img0) | |
| draw = ImageDraw.Draw(img0) | |
| predictions = predict(age_model_ts, model, | |
| stride, imgsz=[320, 320], | |
| conf_thres=0.5, iou_thres=0.45, | |
| source=img0, | |
| with_random_augs = with_random_augs | |
| ) | |
| detections : list[Detection] = [] | |
| for k, bbox in enumerate(predictions): | |
| det = Detection( | |
| (k+1), | |
| bbox["xmin"], | |
| bbox["ymin"], | |
| bbox["xmax"], | |
| bbox["ymax"], | |
| bbox["conf"], | |
| bbox["class"], | |
| bbox["class"], | |
| img0.size | |
| ) | |
| detections.append(det) | |
| draw.rectangle(((det.xmin, det.ymin), (det.xmax, det.ymax)), fill=None, outline=(255,255,255)) | |
| text_length = roboto_font.getlength(bbox["class"]) | |
| rect_center = (det.xmin + det.xmax - text_length) // 2 | |
| draw.rectangle(((rect_center, det.ymin), (rect_center + text_length, det.ymin + text_box_height)), fill=(255,255,255)) | |
| draw.text((rect_center, det.ymin), det.class_name, fill=(0,0,0), font=roboto_font) | |
| return img0 | |
| """ img = Image.open("D:\\Download\\IMG_20220803_153335c2.jpg").convert("RGB") | |
| run_yolo(img) | |
| sys.exit(1) """ | |
| def main(): | |
| input = gr.Image(type='pil', label="Input Image") | |
| outputs = gr.Image(type="pil", label="Output Image", interactive=False) | |
| augment_preds = gr.Checkbox(label="Apply random augmentations") | |
| title = "AgeGuesser" | |
| description = "Guess the age of a person from a facial image!" | |
| article = """ | |
| <p>A fully automated system based on YOLOv5 and EfficientNet to perform face detection and age estimation in real-time.</p> | |
| <p><b>Links</b></p> | |
| <ul> | |
| <li> | |
| <a href='https://link.springer.com/chapter/10.1007/978-3-030-89131-2_25'>Springer</a> | |
| </li> | |
| <li> | |
| <a href='https://www.researchgate.net/publication/355777953_Real-Time_Age_Estimation_from_Facial_Images_Using_YOLO_and_EfficientNet'>Paper</a> | |
| </li> | |
| <li> | |
| <a href='https://github.com/ai-hazard/AgeGuesser-train'>Github</a> | |
| </li> | |
| </ul> | |
| <p>Credits to my dear colleague <a href='https://www.linkedin.com/in/nicola-marvulli-904270136/'>Dott. Nicola Marvulli</a>, we've developed AgeGuesser together as part of two university exams. (Computer Vision + Deep Learning)</p> | |
| <p>Credits to my dear professors and the <a href='https://sites.google.com/site/cilabuniba/'>CILAB</a> research group</p> | |
| <ul> | |
| <li> | |
| <a href='https://sites.google.com/site/cilabuniba/people/giovanna-castellano'>Prof. Giovanna Castellano</a> | |
| </li> | |
| <li> | |
| <a href='https://sites.google.com/view/gennaro-vessio/home-page'>Prof. Gennaro Vessio</a> | |
| </li> | |
| </ul> | |
| """ | |
| examples = [['images/1.jpg', False],['images/2.jpg', False],['images/3.jpg', False],['images/4.jpg', False],['images/5.jpg', False]] | |
| gr.Interface(run_yolo, [input, augment_preds], outputs, title=title, description=description, article=article, examples=examples, theme="huggingface").launch(enable_queue=True, ) # share=True | |
| main() |