first version

app.py

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+import streamlit as st
+import os
+import json
+
+def batch(iterable, n=1):
+    l = len(iterable)
+    for ndx in range(0, l, n):
+        yield iterable[ndx:min(ndx + n, l)]
+
+data_path = "./data/TeTIm-Eval-Mini"
+category_map = {
+    "Digital art": "sampled_art_digital",
+    "Digital sketches": "sampled_art_sketch",
+    "Traditional art": "sampled_art_traditional",
+    "Baroque paintings": "sampled_painting_baroque",
+    "High renaissance paintings": "sampled_painting_high-renaissance",
+    "Neoclassicism paintings": "sampled_painting_neoclassicism",
+    "Animal photography": "sampled_photo_animal",
+    "Food photography": "sampled_photo_food",
+    "Landscape photography": "sampled_photo_landscape",
+    "Portrait photography": "sampled_photo_person"
+}
+models_map = {
+    "real": "Real picture",
+    "DALLE2": "DALL-E 2"
+}
+
+if "current" not in st.session_state:
+    st.session_state["current"] = 1
+
+st.header("TeTIm-Eval-mini showcase")
+category = st.selectbox("Category", category_map.keys())
+
+path = os.path.join(data_path, "real", category_map[category], "images")
+real_images = sorted(os.listdir(path), key=lambda e: int(e.split(".")[0]))
+
+coll, _, colc, _, colr = st.columns(5)
+
+prev = coll.button("« Previous")
+state = colc.empty()
+next = colr.button("Next »")
+
+if prev:
+    st.session_state["current"] = max(st.session_state["current"] - 1, 1)
+
+if next:
+    st.session_state["current"] = min(st.session_state["current"] + 1, len(real_images))
+
+state.write(f"{st.session_state['current']}/{len(real_images)}")
+
+path = os.path.join(data_path, "real", category_map[category], "annotations")
+annotations = sorted(os.listdir(path), key=lambda e: int(e.split(".")[0]))
+
+with open(os.path.join(path, annotations[st.session_state["current"]-1])) as annotation_f:
+    annotation = json.load(annotation_f)
+
+st.subheader(annotation["caption"])
+
+for (modell, modell_name), (modelr, modelr_name) in batch(list(models_map.items()), n=2):
+    coll_title, colr_title = st.columns(2)
+    coll_title.subheader(modell_name)
+    colr_title.subheader(modelr_name)
+
+    pathl = os.path.join(data_path, modell, category_map[category])
+    if modell == "real": pathl = os.path.join(pathl, "images")
+    imagesl = sorted(os.listdir(pathl), key=lambda e: int(e.split(".")[0]))
+
+    pathr = os.path.join(data_path, modelr, category_map[category])
+    if modelr == "real": pathr = os.path.join(pathr, "images")
+    imagesr = sorted(os.listdir(pathr), key=lambda e: int(e.split(".")[0]))
+
+    coll_image, colr_image = st.columns(2)
+    coll_image.image(os.path.join(pathl, imagesl[st.session_state["current"]-1]))
+    colr_image.image(os.path.join(pathr, imagesr[st.session_state["current"]-1]))
+
+