:lipstick: style

app.py

@@ -17,6 +17,7 @@ COLORS = [
     [0.301, 0.745, 0.933],
 ]
 
+
 @st.cache(allow_output_mutation=True)
 def get_hf_components(model_name_or_path):
     feature_extractor = DetrFeatureExtractor.from_pretrained(model_name_or_path)
@@ -24,10 +25,12 @@ def get_hf_components(model_name_or_path):
     model.eval()
     return feature_extractor, model
 
+
 @st.cache
 def get_img_from_url(url):
     return Image.open(requests.get(url, stream=True).raw)
 
+
 def fig2img(fig):
     buf = io.BytesIO()
     fig.savefig(buf)
@@ -54,6 +57,7 @@ def visualize_prediction(pil_img, output_dict, threshold=0.7, id2label=None):
     plt.axis("off")
     return fig2img(plt.gcf())
 
+
 def make_prediction(img, feature_extractor, model):
     inputs = feature_extractor(img, return_tensors="pt")
     outputs = model(**inputs)
@@ -61,6 +65,7 @@ def make_prediction(img, feature_extractor, model):
     processed_outputs = feature_extractor.post_process(outputs, img_size)
     return processed_outputs[0]
 
+
 def main():
     option = st.selectbox("Which model should we use?", ("facebook/detr-resnet-50", "facebook/detr-resnet-101"))
     feature_extractor, model = get_hf_components(option)
@@ -72,5 +77,5 @@ def main():
     st.image(viz_img)
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     main()