fix load image

app.py

@@ -41,22 +41,18 @@ texts = st.text_input('apple, eggs')
 image = ''
 if uploaded_image_zero_file is not None:
     with NamedTemporaryFile() as temp:
-        temp.write(uploaded_image_zero_file.getvalue())
-        temp.seek(0)
         image = Image.open(uploaded_image_zero_file)
         outputImage = np.array(image)
         st.image(outputImage)
-
-if st.button('check tags'):
-    inputs = processor(text=texts, images=image, return_tensors="pt")
-    outputs = model(**inputs)
-    target_sizes = torch.Tensor([image.size[::-1]])
-    results = processor.post_process_object_detection(outputs=outputs, threshold=0.1, target_sizes=target_sizes)
-    i = 0  # Retrieve predictions for the first image for the corresponding text queries
-    text = texts[i]
-    boxes, scores, labels = results[i]["boxes"], results[i]["scores"], results[i]["labels"]
-    st.write(results)
-    # Print detected objects and rescaled box coordinates
-    for box, score, label in zip(boxes, scores, labels):
-        box = [round(i, 2) for i in box.tolist()]
-        print(f"Detected {text[label]} with confidence {round(score.item(), 3)} at location {box}")
+        inputs = processor(text=texts, images=image, return_tensors="pt")
+        outputs = model(**inputs)
+        target_sizes = torch.Tensor([image.size[::-1]])
+        results = processor.post_process_object_detection(outputs=outputs, threshold=0.1, target_sizes=target_sizes)
+        i = 0  # Retrieve predictions for the first image for the corresponding text queries
+        text = texts[i]
+        boxes, scores, labels = results[i]["boxes"], results[i]["scores"], results[i]["labels"]
+        st.write(results)
+        # Print detected objects and rescaled box coordinates
+        for box, score, label in zip(boxes, scores, labels):
+            box = [round(i, 2) for i in box.tolist()]
+            print(f"Detected {text[label]} with confidence {round(score.item(), 3)} at location {box}")