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d0e6c24
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Parent(s):
d0c3bfa
chore: tidy up main
Browse filesremoved unused code, primarily commented out / older versions
- src/main.py +7 -46
src/main.py
CHANGED
@@ -104,18 +104,6 @@ def main() -> None:
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setup_input()
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if 0:## WIP
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# goal of this code is to allow the user to override the ML prediction, before transmitting an observations
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predicted_class = st.sidebar.selectbox("Predicted Class", viewer.WHALE_CLASSES)
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override_prediction = st.sidebar.checkbox("Override Prediction")
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if override_prediction:
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overridden_class = st.sidebar.selectbox("Override Class", viewer.WHALE_CLASSES)
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st.session_state.observations['class_overriden'] = overridden_class
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else:
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st.session_state.observations['class_overriden'] = None
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with tab_map:
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# visual structure: a couple of toggles at the top, then the map inlcuding a
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# dropdown for tileset selection.
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@@ -218,6 +206,13 @@ def main() -> None:
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# 6. manual validation done -> enable the upload buttons
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#
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with tab_inference:
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if st.session_state.MODE_DEV_STATEFUL:
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dbg_show_observation_hashes()
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@@ -292,40 +287,6 @@ def main() -> None:
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# didn't decide what the next state is here - I think we are in the terminal state.
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#st.session_state.workflow_fsm.complete_current_state()
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# inside the inference tab, on button press we call the model (on huggingface hub)
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# which will be run locally.
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# - the model predicts the top 3 most likely species from the input image
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# - these species are shown
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# - the user can override the species prediction using the dropdown
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# - an observation is uploaded if the user chooses.
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# with tab_inference:
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# add_classifier_header()
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# if tab_inference.button("Identify with cetacean classifier"):
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# #pipe = pipeline("image-classification", model="Saving-Willy/cetacean-classifier", trust_remote_code=True)
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# cetacean_classifier = AutoModelForImageClassification.from_pretrained("Saving-Willy/cetacean-classifier",
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# revision=classifier_revision,
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# trust_remote_code=True)
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# if st.session_state.images is None:
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# # TODO: cleaner design to disable the button until data input done?
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# st.info("Please upload an image first.")
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# else:
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# cetacean_classify(cetacean_classifier)
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# inside the hotdog tab, on button press we call a 2nd model (totally unrelated at present, just for demo
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# purposes, an hotdog image classifier) which will be run locally.
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setup_input()
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with tab_map:
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# visual structure: a couple of toggles at the top, then the map inlcuding a
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# dropdown for tileset selection.
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# 6. manual validation done -> enable the upload buttons
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#
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with tab_inference:
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# inside the inference tab, on button press we call the model (on huggingface hub)
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# which will be run locally.
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# - the model predicts the top 3 most likely species from the input image
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# - these species are shown
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# - the user can override the species prediction using the dropdown
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# - an observation is uploaded if the user chooses.
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if st.session_state.MODE_DEV_STATEFUL:
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dbg_show_observation_hashes()
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# didn't decide what the next state is here - I think we are in the terminal state.
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#st.session_state.workflow_fsm.complete_current_state()
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# inside the hotdog tab, on button press we call a 2nd model (totally unrelated at present, just for demo
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# purposes, an hotdog image classifier) which will be run locally.
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