Update app.py

app.py

@@ -1,41 +1,44 @@
-import gradio as gr
 from transformers import DetrImageProcessor, DetrForObjectDetection
 import torch
-from PIL import Image, ImageDraw
+from PIL import Image, ImageDraw, ImageFont  # Import ImageFont
+import gradio as gr
+import requests
 import random
 
 def detect_objects(image):
+    # Load the pre-trained DETR model
     processor = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
     model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
 
     inputs = processor(images=image, return_tensors="pt")
     outputs = model(**inputs)
 
+    # convert outputs (bounding boxes and class logits) to COCO API
+    # let's only keep detections with score > 0.9
     target_sizes = torch.tensor([image.size[::-1]])
     results = processor.post_process_object_detection(outputs, target_sizes=target_sizes, threshold=0.9)[0]
 
+    # Draw bounding boxes and labels on the image
     draw = ImageDraw.Draw(image)
-    labels = []
+    detected_objects = []
     for i, (score, label, box) in enumerate(zip(results["scores"], results["labels"], results["boxes"])):
         box = [round(i, 2) for i in box.tolist()]
         color = (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))
         draw.rectangle(box, outline=color, width=3)
         label_text = f"{model.config.id2label[label.item()]}: {round(score.item(), 2)}"
+        # Larger and bolder font
         draw.text((box[0], box[1]), label_text, fill=color,)
-        labels.append(label_text)
+        detected_objects.append(model.config.id2label[label.item()])
+
+    return image, ', '.join(detected_objects)
 
-    return image, labels
 
 def upload_image(file):
     image = Image.open(file.name)
-    image_with_boxes, labels = detect_objects(image)
-    return image_with_boxes, labels
+    image_with_boxes, detected_objects = detect_objects(image)
+    return image_with_boxes, detected_objects
 
-def show_labels(labels):
-    return "\n".join(labels)
-
-# Interface to display the image with bounding boxes
-iface_objects = gr.Interface(
+iface = gr.Interface(
     fn=upload_image,
     inputs="file",
     outputs=["image", "text"],
@@ -44,24 +47,4 @@ iface_objects = gr.Interface(
     allow_flagging=False
 )
 
-# Interface to display the detected labels
-iface_labels = gr.Interface(
-    fn=show_labels,
-    inputs="text",
-    outputs="text",
-    title="Detected Labels",
-    description="Displays the labels detected in the uploaded image.",
-    allow_flagging=False
-)
-
-# Combine interfaces with a tapped interface
-interface = gr.Interface(
-    [iface_objects, iface_labels],
-    inputs="text",
-    outputs="text",
-    title="Object Detection with Labels",
-    description="Upload an image and view detected objects and labels.",
-    allow_flagging=False
-)
-
-interface.launch()
+iface.launch()