now definition should render

README.md

@@ -22,7 +22,7 @@ pinned: false
 Expected Calibration Error *ECE* is a popular metric to evaluate top-1 prediction miscalibration. 
 It measures the L^p norm difference between a model’s posterior and the true likelihood of being correct.
 
-![ECE definition](./ECE_definition.jpg)
+![ECE definition](https://huggingface.co/spaces/jordyvl/ece/resolve/main/ECE_definition.jpg)
 
 It is generally implemented as a binned estimator that discretizes predicted probabilities into ranges of possible values (bins) for which conditional expectation can be estimated.
 

local_app.py

@@ -61,6 +61,29 @@ metric = ECE()
 Switch inputs and compute_fn
 """
 
+def default_plot():
+    fig = plt.figure()
+    ax1 = plt.subplot2grid((3, 1), (0, 0), rowspan=2)
+    ax2 = plt.subplot2grid((3, 1), (2, 0))
+    ranged = np.linspace(0, 1, 10)
+    ax1.plot(
+        ranged,
+        ranged,
+        color="darkgreen",
+        ls="dotted",
+        label="Perfect",
+    )
+    ax1.set_ylabel("Conditional Expectation")
+    ax1.set_ylim([-0.05, 1.05])  # respective to bin range
+    ax1.legend(loc="lower right")
+    ax1.set_title("Reliability Diagram")
+
+    # Bin frequencies
+    ax2.set_xlabel("Confidence")
+    ax2.set_ylabel("Count")
+    ax2.legend(loc="upper left")  # , ncol=2
+    plt.tight_layout()
+    return fig
 
 def reliability_plot(results):
     fig = plt.figure()
@@ -97,7 +120,8 @@ def reliability_plot(results):
         if np.isnan(empirical):
             continue
 
-        ax1.bar([perfect], height=[empirical], width=-ranged[j], align="edge", color="lightblue")
+        #width=-ranged[j],
+        ax1.bar([perfect], height=[empirical],  align="edge", color="lightblue")
         """
         if perfect == empirical:
             continue
@@ -145,10 +169,11 @@ def compute_and_plot(data, n_bins, bin_range, scheme, proxy, p):
     )
 
     plot = reliability_plot(results)
-    return results["ECE"], plot  # plt.gcf()
+    return results["ECE"], plot
 
 
 outputs = [gr.outputs.Textbox(label="ECE"), gr.Plot(label="Reliability diagram")]
+#outputs[1].value = default_plot().__dict__
 
 iface = gr.Interface(
     fn=compute_and_plot,