multiple image upload app.py

app.py

@@ -191,19 +191,24 @@ def detections_to_json(detections):
         detections_list.append(detection_dict)
     return detections_list
 
-def process_image(image):
+def process_images(images):
     labels = ["insect"]
-    original_image, detections = grounded_segmentation(image, labels, threshold=0.3, polygon_refinement=True)
-    yellow_background_with_insects = create_yellow_background_with_insects(np.array(original_image), detections)
-    detections_json = detections_to_json(detections)
+    results = []
+    json_outputs = []
+    for image in images:
+        original_image, detections = grounded_segmentation(image, labels, threshold=0.3, polygon_refinement=True)
+        yellow_background_with_insects = create_yellow_background_with_insects(np.array(original_image), detections)
+        detections_json = detections_to_json(detections)
+        results.append((yellow_background_with_insects, json.dumps(detections_json, separators=(',', ':'))))
+        json_outputs.append(detections_json)
     json_output_path = "insect_detections.json"
     with open(json_output_path, 'w') as json_file:
-        json.dump(detections_json, json_file, indent=4)
-    return yellow_background_with_insects, json.dumps(detections_json, separators=(',', ':'))
+        json.dump(json_outputs, json_file, indent=4)
+    return results
 
 gr.Interface(
-    fn=process_image,
-    inputs=gr.Image(type="pil"),
-    outputs=[gr.Image(type="numpy"), gr.Textbox()],
+    fn=process_images,
+    inputs=gr.File(file_count="multiple", type="file"),
+    outputs=[gr.Gallery(), gr.Textbox()],
     title="🐞 InsectSAM + GroundingDINO Inference",
 ).launch()