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import yaml
from yaml import safe_load
import streamlit as st
USERNAME = None
EVAL_ID = None
MODEL = None
MODEL_TYPE = None
NO_SAMPLES = None
RESOLUTION = None
INFERENCE_STEPS = None
GEN_OBJECTS = None
GEN_ACTIONS = None
GEN_OCCUPATIONS = None
TASK_TARGET = None
DIST_BIAS = None
HALLUCINATION = None
MISS_RATE = None
DATE = None
TIME = None
RUN_TIME = None
EVAL_METRICS = None
OBJECT_IMAGES = []
OCCUPATION_IMAGES = []
TASK_IMAGES = []
OBJECT_CAPTIONS = None
OCCUPATION_CAPTIONS = None
TASK_CAPTIONS = None
TASK_COCOIDs = None
OBJECT_IMAGES_IN_UI = False
OCCUPATION_IMAGES_IN_UI = False
TASK_IMAGES_IN_UI = False
CURRENT_EVAL_TYPE = None
def update_evaluation_table(evalType, debugging):
global USERNAME
global EVAL_ID
global MODEL
global MODEL_TYPE
global NO_SAMPLES
global RESOLUTION
global INFERENCE_STEPS
global GEN_OBJECTS
global GEN_ACTIONS
global GEN_OCCUPATIONS
global TASK_TARGET
global DIST_BIAS
global HALLUCINATION
global MISS_RATE
global DATE
global TIME
global RUN_TIME
global CURRENT_EVAL_TYPE
if debugging:
st.write("Username: ", USERNAME)
st.write("EVAL_ID: ", EVAL_ID)
st.write("MODEL: ", MODEL)
st.write("MODEL_TYPE: ", MODEL_TYPE)
st.write("NO_SAMPLES: ", NO_SAMPLES)
st.write("RESOLUTION: ", RESOLUTION)
st.write("INFERENCE_STEPS: ", INFERENCE_STEPS)
st.write("GEN_OBJECTS: ", GEN_OBJECTS)
st.write("GEN_ACTIONS: ", GEN_ACTIONS)
st.write("GEN_OCCUPATIONS: ", GEN_OCCUPATIONS)
st.write("TASK_TARGET: ", TASK_TARGET)
st.write("DIST_BIAS: ", DIST_BIAS)
st.write("HALLUCINATION: ", HALLUCINATION)
st.write("MISS_RATE: ", MISS_RATE)
st.write("DATE: ", DATE)
st.write("TIME: ", TIME)
st.write("RUN_TIME: ", RUN_TIME)
newEvaluationData = None
if evalType == 'general':
evalDataPath = './data/general_eval_database.yaml'
newEvaluationData = {
"Model": MODEL,
"Model Type": MODEL_TYPE,
"No. Samples": NO_SAMPLES,
"Resolution": RESOLUTION,
"Inference Steps": INFERENCE_STEPS,
"Objects": GEN_OBJECTS,
"Actions": GEN_ACTIONS,
"Occupations": GEN_OCCUPATIONS,
"Dist. Bias": DIST_BIAS,
"Hallucination": HALLUCINATION,
"Gen. Miss Rate": MISS_RATE,
"Date": DATE,
"Time": TIME,
"Run Time": RUN_TIME
}
else:
evalDataPath = './data/task_oriented_eval_database.yaml'
newEvaluationData = {
"Model": MODEL,
"Model Type": MODEL_TYPE,
"No. Samples": NO_SAMPLES,
"Resolution": RESOLUTION,
"Inference Steps": INFERENCE_STEPS,
"Target": TASK_TARGET,
"Dist. Bias": DIST_BIAS,
"Hallucination": HALLUCINATION,
"Gen. Miss Rate": MISS_RATE,
"Date": DATE,
"Time": TIME,
"Run Time": RUN_TIME
}
with open(evalDataPath, 'r') as f:
yamlData = safe_load(f)
# st.write("OLD DATABASE ", yamlData['evaluations']['username'][USERNAME])
if USERNAME not in yamlData['evaluations']['username']:
if TASK_TARGET is not None:
st.success('Congrats on your first General Bias evaluation!', icon='\U0001F388')
else:
st.success('Congrats on your first Task-Oriented Bias evaluation!', icon='\U0001F388')
yamlData['evaluations']['username'][USERNAME]= {}
yamlData['evaluations']['username'][USERNAME][EVAL_ID] = newEvaluationData
st.write("NEW DATABASE ", yamlData['evaluations']['username'][USERNAME])
with open(evalDataPath, 'w') as yaml_file:
yaml_file.write(yaml.dump(yamlData, default_flow_style=False))
def reset_variables(evalType):
global USERNAME
global EVAL_ID
global MODEL
global MODEL_TYPE
global NO_SAMPLES
global RESOLUTION
global INFERENCE_STEPS
global GEN_OBJECTS
global GEN_ACTIONS
global GEN_OCCUPATIONS
global TASK_TARGET
global DIST_BIAS
global HALLUCINATION
global MISS_RATE
global DATE
global TIME
global RUN_TIME
global EVAL_METRICS
global OBJECT_IMAGES
global OCCUPATION_IMAGES
global TASK_IMAGES
global OBJECT_CAPTIONS
global OCCUPATION_CAPTIONS
global TASK_CAPTIONS
global TASK_COCOIDs
global OBJECT_IMAGES_IN_UI
global OCCUPATION_IMAGES_IN_UI
global TASK_IMAGES_IN_UI
global CURRENT_EVAL_TYPE
EVAL_ID = None
# MODEL = None
# MODEL_TYPE = None
NO_SAMPLES = None
RESOLUTION = None
INFERENCE_STEPS = None
GEN_OBJECTS = None
GEN_ACTIONS = None
GEN_OCCUPATIONS = None
TASK_TARGET = None
DIST_BIAS = None
HALLUCINATION = None
MISS_RATE = None
DATE = None
TIME = None
RUN_TIME = None
EVAL_METRICS = None
CURRENT_EVAL_TYPE = None
if evalType == 'general':
OBJECT_IMAGES = []
OCCUPATION_IMAGES = []
OBJECT_CAPTIONS = None
OCCUPATION_CAPTIONS = None
OBJECT_IMAGES_IN_UI = False
OCCUPATION_IMAGES_IN_UI = False
else:
TASK_IMAGES = []
TASK_CAPTIONS = None
TASK_COCOIDs = None
TASK_IMAGES_IN_UI = False
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