update description

app.py

@@ -14,17 +14,16 @@ torch.hub.download_url_to_file(age_model, 'age_model.pt')
 sys.path.append("./")
 sys.path.append("./yolov5")
 
-age_model_ts = torch.jit.load("age_model.pt")
-
 from yolov5.detect import predict, load_yolo_model
 
-# 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")
+
+roboto_font = ImageFont.truetype("Roboto-Regular.ttf")
 
 def run_yolo(img):
 
-    #img0 = Image.open(img.name).convert("RGB")
     img_path = img.name # ["name"]
     img0 = Image.open(img_path).convert("RGB")
     draw = ImageDraw.Draw(img0)
@@ -35,8 +34,6 @@ def run_yolo(img):
     detections : list[Detection] = []
     for k, (bboxes, img)  in enumerate(predictions):
         
-        #print(bboxes)
-        # exp.imgs.append(img_info)
         for i, bbox in enumerate(bboxes):
             det = Detection(
                 (k+1)*(i+1),
@@ -55,7 +52,7 @@ def run_yolo(img):
                 detections.append(det)
                 draw.rectangle(((det.xmin, det.ymin), (det.xmax, det.ymax)), fill=None, outline=(255,255,255))
                 draw.rectangle(((det.xmin, det.ymin - 10), (det.xmax, det.ymin)), fill=(255,255,255))
-                draw.text((det.xmin, det.ymin - 10), det.class_name, fill=(0,0,0), font=ImageFont.truetype("Roboto-Regular.ttf"))
+                draw.text((det.xmin, det.ymin - 10), det.class_name, fill=(0,0,0), font=roboto_font)
 
     return img0
 
@@ -63,12 +60,15 @@ inputs = gr.inputs.Image(type='file', label="Input Image")
 outputs = gr.outputs.Image(type="pil", label="Output Image")
 
 title = "AgeGuesser"
-description = "Guess the age of a person!"
-article = """A fully automated system based on YOLOv5 and EfficientNet to perform face detection and age estimation in real-time. 
-    Links:
+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'>Paper</a>
+            <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> 
@@ -77,6 +77,21 @@ article = """A fully automated system based on YOLOv5 and EfficientNet to perfor
             <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'], ['images/2.jpg'], ['images/3.jpg'], ['images/4.jpg'], ['images/5.jpg'], ]