dev(narugo): add percentile value

app.py

@@ -36,6 +36,17 @@ def _get_mark_table(model):
     return x, y
 
 
+def _get_percentile(x, y, v):
+    idx = np.searchsorted(x, np.clip(v, a_min=0.0, a_max=6.0))
+    if idx < x.shape[0] - 1:
+        x0, y0 = x[idx], y[idx]
+        x1, y1 = x[idx + 1], y[idx + 1]
+        return np.clip((v - x0) / (x1 - x0) * (y1 - y0) + y0, a_min=0.0, a_max=1.0)
+
+    else:
+        return y[idx]
+
+
 def _fn_predict(image, model):
     scores = classify_predict_score(
         image=image,
@@ -44,7 +55,7 @@ def _fn_predict(image, model):
     )
     weighted_mean = sum(i * scores[label] for i, label in enumerate(LABELS))
     x, y = _get_mark_table(model)
-    percentile = y[np.searchsorted(x, np.clip(weighted_mean, a_min=0.0, a_max=6.0))]
+    percentile = _get_percentile(x, y, weighted_mean)
     return weighted_mean, percentile, scores