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cathyxl
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a05992b
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Parent(s):
b856a17
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Browse files
app.py
ADDED
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import json
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import os
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import os.path as osp
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import gradio as gr
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import numpy as np
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import gradio as gr
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def load_json(load_dir_path, json_file_name):
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load_path = os.path.join(load_dir_path, json_file_name)
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if not os.path.exists(load_path):
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return None
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with open(load_path, 'r', encoding='utf-8') as f:
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obj_serializable = json.load(f)
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return obj_serializable
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def load_results_recaption(save_path, model="gpt-3.5-turbo-0125"):
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result_list = load_json(save_path, f'final_results-{model}.json')
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if result_list is not None:
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result_list = result_list['result_list']
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if result_list is None:
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result_list = load_json(save_path, 'inference_results.json')
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return result_list
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plava_theme = gr.themes.Monochrome(
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text_size="sm",
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spacing_size="sm",
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primary_hue=gr.themes.Color(c100="#f5f5f5", c200="#e5e5e5", c300="#d4d4d4", c400="#a3a3a3", c50="#fafafa", c500="#737373", c600="#525252", c700="#404040", c800="#262626", c900="#171717", c950="#000000"),
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secondary_hue=gr.themes.Color(c100="#f5f5f5", c200="#e5e5e5", c300="#d4d4d4", c400="#a3a3a3", c50="#fafafa", c500="#737373", c600="#525252", c700="#404040", c800="#262626", c900="#171717", c950="#000000"),
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neutral_hue=gr.themes.Color(c100="#f5f5f5", c200="#e5e5e5", c300="#d4d4d4", c400="#a3a3a3", c50="#fafafa", c500="#737373", c600="#525252", c700="#404040", c800="#262626", c900="#171717", c950="#000000"),
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).set(
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background_fill_primary_dark='*primary_950',
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background_fill_secondary_dark='*neutral_950'
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)
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load_results_funcs = [
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load_results_recaption,
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]
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recaption_root_dir = "recaption_results"
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local_video_root_dir = "DATAS/Recaption/Inter4K/60fps/UHD"
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remote_video_root_dir ="https://huggingface.co/datasets/ermu2001/Inter4kPlavaRecaption/resolve/main/DATAS/Recaption/Inter4K/60fps/UHD"
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def show(result_list_first, result_list_second, result_index):
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sample2index_second = {}
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for i, result in enumerate(result_list_second):
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if 'video_path' not in result:
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continue
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question = result['question'] if 'question' in result else ''
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video_path = result['video_path']
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samplehash = question + '--' +video_path
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sample2index_second[samplehash] = i
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info = result_list_first[result_index]
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info_str_first = json.dumps(info, indent=4, ensure_ascii=False)
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video_path = info['video_path']
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question = info['question'] if 'question' in info else ''
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samplehash = question + '--' +video_path
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if samplehash in sample2index_second:
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info = result_list_second[sample2index_second[samplehash]]
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info_str_second = json.dumps(info, indent=4, ensure_ascii=False)
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else:
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info_str_second = f"NO {video_path} IN THE SECOND RESULT DIR"
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video_path = video_path.replace(local_video_root_dir, remote_video_root_dir)
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video_path = "https://huggingface.co/datasets/nielsr/video-demo/resolve/main/eating_spaghetti.mp4"
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return video_path, info_str_first, info_str_second
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def reload_results_dirs():
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result_dirs = []
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# load result dir paths
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for dirpath, dirnames, filenames in os.walk(recaption_root_dir):
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if len(dirnames) == 0 and len(filenames) != 0:
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result_dirs.append(dirpath)
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return gr.Dropdown(result_dirs, value=result_dirs[0])
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def reload_results(result_dir):
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# if isinstance(result_dir, list):
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# result_dir = result_dir[0]
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if result_dir is None or not osp.exists(result_dir):
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return None
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for fn in load_results_funcs:
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result_list = fn(result_dir)
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if result_list is not None:
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np.random.shuffle(result_list)
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break
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result_index = gr.Slider(0, len(result_list), step=1)
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return result_list, result_index
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with gr.Blocks(title="PLAVA RESULTS", theme=plava_theme) as demo:
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result_list_first = gr.State()
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result_list_second = gr.State()
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with gr.Row():
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with gr.Column():
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gr.Markdown("# Showing off Model's Outputs.")
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gr.Markdown(
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"You can find all our results, including:\n"
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"1. results of Captioned Inter4k\n"
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"2. results of Different Benchmark inference outputs.\n"
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"Choose a directory to see the different output variant.\n"
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"You can also choose secondary directory (as long as they are from the same dataset.) to compare on the results.\n"
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)
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with gr.Row():
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with gr.Column():
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show_video = gr.Video(interactive=False)
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with gr.Column():
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button_reload = gr.Button(value='Reload From The Evaluation/Inference Root Directory')
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result_index = gr.Slider(0, 0, step=1, label="Index")
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result_dir_first = gr.Dropdown(label='Test Result Path')
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info_first = gr.Text(interactive=False, label='Detailed Output Information')
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result_dir_second = gr.Dropdown(label='Test Result Path')
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info_second = gr.Text(interactive=False, label='Detailed Output Information')
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button_reload.click(reload_results_dirs, [], [result_dir_first])
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button_reload.click(reload_results_dirs, [], [result_dir_second])
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result_dir_first.change(reload_results, [result_dir_first], [result_list_first, result_index])
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result_dir_second.change(reload_results, [result_dir_second], [result_list_second, result_index])
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result_index.change(show, [result_list_first, result_list_second, result_index], [show_video, info_first, info_second])
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demo.load(reload_results_dirs, [], [result_dir_first])
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demo.load(reload_results_dirs, [], [result_dir_second])
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demo.launch()
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recaption_results/recaption_inter4k/inference_results.json
ADDED
The diff for this file is too large to render.
See raw diff
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recaption_results/recaption_inter4k_ch/inference_results.json
ADDED
The diff for this file is too large to render.
See raw diff
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requirements.txt
ADDED
@@ -0,0 +1,2 @@
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gradio
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2 |
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numpy
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