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a08dd7a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 | import gradio as gr
import json
import bisect
import time
import threading
# Define the questions with a single image for options
with open('spatial/questions.json', 'r') as q_file:
questions = json.load(q_file)
with open('spatial/answers.json', 'r') as a_file:
answers = json.load(a_file)
with open('spatial/distribution.json', 'r') as file:
distribution_data = json.load(file)
def calculate_percentile(correct_answers, distribution):
# Sort the distribution by the number of correct answers
distribution.sort(key=lambda x: x[0])
# Separate the correct answers and percentiles into two lists
scores = [item[0] for item in distribution]
percentiles = [item[1] for item in distribution]
# Find the index where the given correct_answers should be inserted
index = bisect.bisect_left(scores, correct_answers)
# If the exact score is found in the distribution
if index < len(scores) and scores[index] == correct_answers:
return percentiles[index]
# If the score is beyond the highest score in the distribution
if index == len(scores):
return 100.0
# If the score is between two values in the distribution, interpolate
if index > 0:
lower_score, lower_percentile = scores[index-1], percentiles[index-1]
upper_score, upper_percentile = scores[index], percentiles[index]
# Linear interpolation
slope = (upper_percentile - lower_percentile) / (upper_score - lower_score)
interpolated_percentile = lower_percentile + slope * (correct_answers - lower_score)
return round(interpolated_percentile, 2)
# If the score is below the lowest score in the distribution
return 0.0
# Function to evaluate the answer
def evaluate_answer(*responses):
score = 0
distribution = [(item['correct_answers'], item['percentile']) for item in distribution_data]
if any(response is None for response in responses):
indices = [index for index, value in enumerate(responses) if value is None]
indices = [value + 1 for value in indices]
raise gr.Error(f"No se puede quedar ningun valor en 0. Preguntas sin respuesta:{indices}")
for i, response in enumerate(responses):
response_parsed = response.split('.')[0]
if response_parsed == answers[str(i)]:
score += 1
percentile = calculate_percentile(score, distribution)
return f"Your score: {percentile}: correct answers: {score}"
# Create a Gradio interface
with gr.Blocks() as demo:
results = []
for question in questions:
with gr.Row():
with gr.Column():
gr.Image(type="filepath",
label=f"Question {questions.index(question) + 1}",
value=question["question"],
show_download_button=False,
mirror_webcam=False,
sources=['clipboard'],
interactive=False)
with gr.Column():
gr.Image(type="filepath", label="Options",
value=question["options"],
mirror_webcam=False,
show_download_button=False,
sources=['clipboard'],
interactive=False)
radio = gr.Radio(choices=["A", "B", "C", "D"],
label="Choose an option")
results.append(radio)
submit = gr.Button("Submit")
output = gr.Textbox(label="Results")
submit.click(evaluate_answer, inputs=results, outputs=output)
# Launch the interface
if __name__ == "__main__":
#app = create_interface()
demo.launch()
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