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from glob import glob
import json
import numpy as np
import gradio as gr
def calculate_the_results():
all_jsons_path = glob('./responses/*.json')
all_jsons = [json.load(open(path)) for path in all_jsons_path]
# count number of user corrects for each json and average and also calcaulte the type of NNs
top1_results = []
top1_acc = []
topK_results = []
topK_acc = []
for js in all_jsons:
# read one key and determine the type of NN
type_of_NNs = js['history'][0]['type']
if type_of_NNs == 'topK':
acc = np.mean([js['history'][x]['is_user_correct'] for x in range(len(js['history']))])
topK_acc.append((acc*100).round(2))
topK_results.append(js)
else:
top1_results.append(js)
acc = np.mean([js['history'][x]['is_user_correct'] for x in range(len(js['history']))])
top1_acc.append((acc*100).round(2))
print('# of top1: ', len(top1_results))
print('top1 Accuracy: ', top1_acc)
# print std and mean of top1_acc
std = np.std(top1_acc)
mean = np.mean(top1_acc)
print('top1 std: ', std)
print('top1 mean: ', mean)
print('----------------------------------')
print('# of topK: ', len(topK_results))
print('topK Accuracy: ', topK_acc)
std = np.std(topK_acc)
mean = np.mean(topK_acc)
print('topK std: ', std)
print('topK mean: ', mean)
def calculate_the_results():
all_jsons_path = glob('./responses/*.json')
all_jsons = [json.load(open(path)) for path in all_jsons_path]
# count number of user corrects for each json and average and also calculate the type of NNs
top1_results = []
top1_acc = []
topK_results = []
topK_acc = []
for js in all_jsons:
# read one key and determine the type of NN
type_of_NNs = js['history'][0]['type']
if type_of_NNs == 'topK':
acc = np.mean([js['history'][x]['is_user_correct'] for x in range(len(js['history']))])
topK_acc.append((acc*100).round(2))
topK_results.append(js)
else:
top1_results.append(js)
acc = np.mean([js['history'][x]['is_user_correct'] for x in range(len(js['history']))])
top1_acc.append((acc*100).round(2))
top1_output = f"# of top1: {len(top1_results)}\ntop1 Accuracy: {top1_acc}\ntop1 std: {np.std(top1_acc)}\ntop1 mean: {np.mean(top1_acc)}\n----------------------------------\n"
topK_output = f"# of topK: {len(topK_results)}\ntopK Accuracy: {topK_acc}\ntopK std: {np.std(topK_acc)}\ntopK mean: {np.mean(topK_acc)}"
return top1_output + topK_output
with gr.Blocks(theme=gr.themes.Soft()) as demo:
update_btn = gr.Button("Calculate the results")
results_textbox = gr.Textbox(lines=10, label="Results")
update_btn.click(fn=calculate_the_results, outputs=results_textbox)
demo.launch(debug=False, server_name="0.0.0.0", server_port=9911) |