Upload object_detection.py

object_detection.py

@@ -0,0 +1,27 @@
+# from PIL import Image
+from transformers import DetrFeatureExtractor
+from transformers import DetrForObjectDetection
+import torch
+# import numpy as np
+
+def object_count(picture):
+
+    feature_extractor = DetrFeatureExtractor.from_pretrained("facebook/detr-resnet-50")
+    encoding = feature_extractor(picture, return_tensors="pt")
+    model = DetrForObjectDetection.from_pretrained("facebook/detr-resnet-50")
+    outputs = model(**encoding)
+    # keep only predictions of queries with 0.9+ confidence (excluding no-object class)
+    probas = outputs.logits.softmax(-1)[0, :, :-1]
+    keep = probas.max(-1).values > 0.7
+    count = 0
+    for i in keep:
+        if i:
+            count=count+1
+
+    return "About " + str(count) +" common objects were detected"
+
+# object_count("toothbrush.jpg")
+import gradio as gr
+
+interface = gr.Interface(object_count, gr.inputs.Image(shape=(640, 480)), "text").launch()
+