DataViz / app.py
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import os
import re
import json
import streamlit as st
from PIL import Image, ImageDraw
import requests
from io import BytesIO
import seaborn as sns
import matplotlib.pyplot as plt
from streamlit_chat import message as st_message
import yaml
st.set_page_config(page_title="Data Exploration", page_icon="🌍", layout="wide", initial_sidebar_state="collapsed")
COLORS = sns.color_palette("Paired", n_colors=100).as_hex()
def load_config(config_fn, field='data_explore') -> dict:
config = yaml.load(open(config_fn), Loader=yaml.Loader)
return config[field]
def convert_from_prompt_tokens(s_with_region_tokens):
"""Convert from strings with prompt tokens for prompt encoders
e.g.:
Input: "<Region><L12><24><L101><L777></Region>"
Output: [0.012, 0.024, 0.101, 0.777]
"""
REGION_PATTERN = r'<Region>(\s*<L(\d{1,4})>\s*<L(\d{1,4})>\s*<L(\d{1,4})>\s*<L(\d{1,4})>\s*)</Region>'
boxes = []
boxes_str = re.findall(REGION_PATTERN, s_with_region_tokens)
for boxes_str_i in boxes_str:
matched_str_i, boxes_str_i = boxes_str_i[0], boxes_str_i[1:]
boxes.append(tuple([int(s)/1000 for s in boxes_str_i]))
return boxes
def parse_regions(s):
pattern = r"\[([\d.,\s]+)\]"
matches = re.findall(pattern, s)
bboxes = []
points = []
for res in matches:
res = eval(res)
if len(res) == 4:
# bbox
x1, y1, x2, y2 = res
bboxes.append((x1, y1, x2, y2))
else:
x1, y1 = res
points.append((x1, y1))
bboxes.extend(convert_from_prompt_tokens(s))
return list(set(bboxes))
def get_image(image_path, bboxes=None):
if os.path.exists(image_path):
image = Image.open(image_path).convert('RGB')
else:
# 从URL获取图片
response = requests.get(image_path)
image = Image.open(BytesIO(response.content)).convert('RGB')
draw = ImageDraw.Draw(image, 'RGB')
color_mapping = None
if bboxes is not None:
width, height = image.size
color_mapping = []
for i, bbox_coords in enumerate(bboxes):
color = COLORS[i]
x1, y1, x2, y2 = bbox_coords
x1 *= width
y1 *= height
x2 *= width
y2 *= height
draw.rectangle([x1, y1, x2, y2], outline=color, width=3)
color_mapping.append([bbox_coords, color])
color_mapping = dict(color_mapping)
return image, color_mapping
def insert_color(s, color_mapping):
for coords, color in color_mapping.items():
coords_str = ', '.join([str(x) for x in coords])
s = s.replace('[' + coords_str + ']', f'<span style="color: {color}; font-weight: bold;">■</span>' + ' [' + coords_str + ']')
return s
modal_indicator = ['<image>', '<audio>', '<video>']
def show_one_msg(msg, modal_inputs):
splits = re.split('(' + '|'.join(modal_indicator) + ')', msg)
for s in splits:
if s == '<image>':
st.image(modal_inputs['image'].pop(0))
elif s == '<audio>':
st.audio(modal_inputs['audio'].pop(0))
elif s == '<video>':
st.video(modal_inputs['video'].pop(0))
else:
st.write(s)
def show_multimodal_example(example, col1, col2):
with col1:
info = example.get('info', {})
info['modal_inputs'] = example['modal_inputs']
st.json(info)
with col2:
conversations = example['conversations']
modal_inputs = example['modal_inputs']
for i in range(len(conversations) // 2):
with st.chat_message("user"):
show_one_msg(conversations[2*i]['value'], modal_inputs)
with st.chat_message("assistant"):
show_one_msg(conversations[2*i+1]['value'], modal_inputs)
def show_example(example, col1, col2, enable_scores=True):
if 'conversations' in example:
regions = parse_regions(str(example['conversations']))
else:
regions = parse_regions(str(example))
image_fn = example['image']
image, color_mapping = get_image(image_fn, regions)
with col1:
st.image(image)
info = example.get('info', {})
info['id'] = example.get('id', 'N/A')
info['image'] = image_fn
if 'dataset' in example:
info['source'] = example['dataset']
st.json(info)
if len(color_mapping):
table_md = "| 颜色 | 坐标 |\n| --- | --- |\n"
for coords, color in color_mapping.items():
color_cell = f'<span style="color: {color}; font-weight: bold;">■</span>'
table_md += f"| {color_cell} | {coords} |\n"
# 使用Markdown显示表格
st.markdown(table_md, unsafe_allow_html=True)
score_dict = None
with col2:
if 'conversations' in example:
if enable_scores:
score_dict = {'image': image_fn, 'conversations': example['conversations']}
with st.expander("Give a score based on the result above", expanded=True):
quality_score = st.radio("问题质量分数",('Bad', 'Mediocre', 'Good'),key="quality", horizontal = True)
format_score = st.radio("格式分数",('Bad', 'Mediocre', 'Good'),key="format", horizontal = True)
score_dict['scores'] = {
'quality': quality_score, 'format': format_score
}
st.subheader("Chat")
conversations = example['conversations']
for i in range(len(conversations) // 2):
st_message(conversations[2*i]['value'], is_user=True, key=image_fn + str(2*i))
st_message(conversations[2*i+1]['value'], is_user=False, key=image_fn + str(2*i+1))
if 'ground_truth' in example:
# 显示查询
gt = insert_color(json.dumps(example['ground_truth']), color_mapping)
st.markdown(f"**Ground Truth:**\n\n{gt}", unsafe_allow_html=True)
else:
# 显示指令
instruction = insert_color(example['instruction'], color_mapping)
st.markdown(f"**Instruction:**\n\n{instruction}", unsafe_allow_html=True)
# 显示输入
if 'input' in example:
input = insert_color(example['input'], color_mapping)
st.markdown(f"**Input:**\n\n{input}", unsafe_allow_html=True)
# 显示输出
output = insert_color(example['output'], color_mapping)
st.markdown(f"**Output:**\n\n{output}", unsafe_allow_html=True)
if 'query' in example:
# 显示查询
query = insert_color(json.dumps(example['query']), color_mapping)
st.markdown(f"**Query:**\n\n{query}", unsafe_allow_html=True)
return score_dict
def reset_state():
print('RESET')
st.session_state['data_explore'] = {'idx': 0}
st.session_state.scores = {}
def load_dir_data(dir, dataset_configs):
mapping_file = os.path.join(dir, 'mapping.yaml')
assert os.path.exists(mapping_file)
config = yaml.load(open(mapping_file), Loader=yaml.Loader)
# image_paths = dataset_configs
image_paths = config['image_paths']
image_paths['default'] = image_paths.get('default', '.')
res = []
for k, v in config['mapping'].items():
if os.path.exists(os.path.join(dir, k + '.json')):
data = json.load(open(os.path.join(dir, k + '.json')))
elif os.path.exists(os.path.join(dir, k + '.jsonl')):
data = [json.loads(line) for line in open(os.path.join(dir, k + '.jsonl'))]
elif os.path.exists(os.path.join(dir, k + '.txt')):
data = [json.loads(line) for line in open(os.path.join(dir, k + '.txt'))]
image_path = image_paths.get(v, image_paths['default'])
for example in data:
example['image'] = os.path.join(image_path, example['image'])
example['dataset'] = k
res.extend(data)
return res
@st.cache_data
def load_data(fn, dataset_configs):
if os.path.isdir(fn):
res = load_dir_data(fn, dataset_configs)
return res
if fn.endswith(('.txt', '.jsonl')):
res = []
for line in open(fn):
example = json.loads(line)
res.append(example)
else:
res = json.load(open(fn))
for example in res:
dataset_path = dataset_configs[example.get('dataset', 'default')]
if 'image' in example:
example['image'] = os.path.join(dataset_path, example['image'])
elif 'img_info' in example:
if isinstance(example['img_info'], str):
example['image'] = os.path.join(dataset_path, example['img_info'])
else:
if 'coco_url' in example['img_info']:
example['image'] = example['img_info']['coco_url']
else:
assert 'modal_inputs' in example
return res
dataset_configs = load_config('config.yaml')
print(dataset_configs)
data_paths = dataset_configs.get('data_paths', ['instruction_data'])
files = []
def add_file(path):
if os.path.exists(os.path.join(path, 'mapping.yaml')):
files.append(path)
else:
for f in sorted(os.listdir(path)):
file = os.path.join(path, f)
if os.path.isfile(file) and file.endswith(('.txt', '.json')):
files.append(file)
else:
add_file(file)
for data_path in data_paths:
add_file(data_path)
st.session_state['data_explore'] = {'idx': 0}
enable_score = st.sidebar.checkbox('Score it!', value=False)
if enable_score and 'scores' not in st.session_state:
st.session_state.scores = {}
status_placeholder = st.empty()
control_col1, control_col2 = st.columns(2)
with control_col1:
selected_file = st.selectbox('Select a file', files, on_change=reset_state)
col1, col2 = st.columns(2)
if selected_file:
data = load_data(selected_file, dataset_configs)
with control_col2:
idx = st.number_input(f'Input an idx (Total: {len(data)})', min_value=0, max_value=len(data), value=st.session_state.get('data_explore', {}).get('idx', 0))
st.session_state['data_explore']['idx'] = idx
if 'image' in data[idx]:
show_example(data[idx], col1, col2, enable_scores=enable_score)
else:
show_multimodal_example(data[idx], col1, col2)
if enable_score:
name = st.sidebar.text_input("Username", placeholder = "Enter your name", value="cc")
if st.sidebar.button(label ="Submit scores", key = "submit"):
if name:
score_path = f"score_results/{os.path.basename(selected_file)}_{name}.json"
with open(score_path, "w") as score_file:
json.dump(st.session_state.scores, score_file, indent = 4)
status_placeholder.success("Successfully saved!")
else:
status_placeholder.error("Please enter your name on the sidebar!")