locsec/AMMICO
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AMMICO/build/doctrees/nbsphinx/notebooks/Example summary.ipynb

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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Image summary and visual question answering"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"This notebooks shows some preliminary work on Image Captioning and Visual question answering with lavis. It is mainly meant to explore its capabilities and to decide on future research directions. We package our code into a `ammico` package that is imported here:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T09:58:02.193945Z",
"iopub.status.busy": "2023-05-05T09:58:02.193652Z",
"iopub.status.idle": "2023-05-05T09:58:15.239027Z",
"shell.execute_reply": "2023-05-05T09:58:15.238177Z"
},
"tags": []
},
"outputs": [],
"source": [
"from ammico import utils as mutils\n",
"from ammico import display as mdisplay\n",
"import ammico.summary as sm"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Set an image path as input file path."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T09:58:15.243270Z",
"iopub.status.busy": "2023-05-05T09:58:15.242475Z",
"iopub.status.idle": "2023-05-05T09:58:15.247584Z",
"shell.execute_reply": "2023-05-05T09:58:15.246840Z"
},
"tags": []
},
"outputs": [],
"source": [
"images = mutils.find_files(\n",
" path=\"data/\",\n",
" limit=10,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T09:58:15.251131Z",
"iopub.status.busy": "2023-05-05T09:58:15.250641Z",
"iopub.status.idle": "2023-05-05T09:58:15.254428Z",
"shell.execute_reply": "2023-05-05T09:58:15.253624Z"
},
"tags": []
},
"outputs": [],
"source": [
"mydict = mutils.initialize_dict(images)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create captions for images and directly write to csv"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here you can choose between two models: \"base\" or \"large\""
]
},
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"shell.execute_reply": "2023-05-05T09:59:07.180129Z"
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"tags": []
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"\n"
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],
"source": [
"obj = sm.SummaryDetector(mydict)\n",
"summary_model, summary_vis_processors = obj.load_model(\"base\")\n",
"# summary_model, summary_vis_processors = obj.load_model(\"large\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T09:59:07.187735Z",
"iopub.status.busy": "2023-05-05T09:59:07.186982Z",
"iopub.status.idle": "2023-05-05T09:59:44.639515Z",
"shell.execute_reply": "2023-05-05T09:59:44.638665Z"
},
"tags": []
},
"outputs": [],
"source": [
"for key in mydict:\n",
" mydict[key] = sm.SummaryDetector(mydict[key]).analyse_image(\n",
" summary_model, summary_vis_processors\n",
" )"
]
},
{
"cell_type": "markdown",
"metadata": {
"tags": []
},
"source": [
"Convert the dictionary of dictionaries into a dictionary with lists:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T09:59:44.643845Z",
"iopub.status.busy": "2023-05-05T09:59:44.643351Z",
"iopub.status.idle": "2023-05-05T09:59:44.649585Z",
"shell.execute_reply": "2023-05-05T09:59:44.648822Z"
},
"tags": []
},
"outputs": [],
"source": [
"outdict = mutils.append_data_to_dict(mydict)\n",
"df = mutils.dump_df(outdict)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Check the dataframe:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T09:59:44.653200Z",
"iopub.status.busy": "2023-05-05T09:59:44.652719Z",
"iopub.status.idle": "2023-05-05T09:59:44.668496Z",
"shell.execute_reply": "2023-05-05T09:59:44.667754Z"
},
"tags": []
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>filename</th>\n",
" <th>const_image_summary</th>\n",
" <th>3_non-deterministic summary</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>data/102141_2_eng.png</td>\n",
" <td>a collage of images including a corona sign, a...</td>\n",
" <td>[a collage of pictures with medical equipment,...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>data/106349S_por.png</td>\n",
" <td>a man wearing a face mask while looking at a c...</td>\n",
" <td>[a man with a medical mask on while looking at...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>data/102730_eng.png</td>\n",
" <td>two people in blue coats spray disinfection a van</td>\n",
" <td>[a couple of people in blue coats spray water,...</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" filename const_image_summary \n",
"0 data/102141_2_eng.png a collage of images including a corona sign, a... \\\n",
"1 data/106349S_por.png a man wearing a face mask while looking at a c... \n",
"2 data/102730_eng.png two people in blue coats spray disinfection a van \n",
"\n",
" 3_non-deterministic summary \n",
"0 [a collage of pictures with medical equipment,... \n",
"1 [a man with a medical mask on while looking at... \n",
"2 [a couple of people in blue coats spray water,... "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head(10)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Write the csv file:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T09:59:44.672582Z",
"iopub.status.busy": "2023-05-05T09:59:44.672297Z",
"iopub.status.idle": "2023-05-05T09:59:44.678724Z",
"shell.execute_reply": "2023-05-05T09:59:44.678005Z"
},
"tags": []
},
"outputs": [],
"source": [
"df.to_csv(\"./data_out.csv\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Manually inspect the summaries\n",
"\n",
"To check the analysis, you can inspect the analyzed elements here. Loading the results takes a moment, so please be patient. If you are sure of what you are doing.\n",
"\n",
"`const_image_summary` - the permanent summarys, which does not change from run to run (analyse_image).\n",
"\n",
"`3_non-deterministic summary` - 3 different summarys examples that change from run to run (analyse_image). "
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T09:59:44.682194Z",
"iopub.status.busy": "2023-05-05T09:59:44.681914Z",
"iopub.status.idle": "2023-05-05T09:59:45.647984Z",
"shell.execute_reply": "2023-05-05T09:59:45.646959Z"
},
"tags": []
},
"outputs": [
{
"ename": "AttributeError",
"evalue": "module 'ammico.display' has no attribute 'explore_analysis'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[9], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mmdisplay\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexplore_analysis\u001b[49m(mydict, identify\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msummary\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
"\u001b[0;31mAttributeError\u001b[0m: module 'ammico.display' has no attribute 'explore_analysis'"
]
}
],
"source": [
"mdisplay.explore_analysis(mydict, identify=\"summary\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Generate answers to free-form questions about images written in natural language. "
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Set the list of questions"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T09:59:45.652541Z",
"iopub.status.busy": "2023-05-05T09:59:45.651815Z",
"iopub.status.idle": "2023-05-05T09:59:45.657216Z",
"shell.execute_reply": "2023-05-05T09:59:45.656471Z"
}
},
"outputs": [],
"source": [
"list_of_questions = [\n",
" \"How many persons on the picture?\",\n",
" \"Are there any politicians in the picture?\",\n",
" \"Does the picture show something from medicine?\",\n",
"]"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T09:59:45.660673Z",
"iopub.status.busy": "2023-05-05T09:59:45.660151Z",
"iopub.status.idle": "2023-05-05T10:00:56.016821Z",
"shell.execute_reply": "2023-05-05T10:00:56.014222Z"
}
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},
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"\r",
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},
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"\r",
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"\r",
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]
},
{
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"output_type": "stream",
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"\r",
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},
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},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\n"
]
}
],
"source": [
"for key in mydict:\n",
" mydict[key] = sm.SummaryDetector(mydict[key]).analyse_questions(list_of_questions)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T10:00:56.031144Z",
"iopub.status.busy": "2023-05-05T10:00:56.030259Z",
"iopub.status.idle": "2023-05-05T10:00:56.378410Z",
"shell.execute_reply": "2023-05-05T10:00:56.377571Z"
}
},
"outputs": [
{
"ename": "AttributeError",
"evalue": "module 'ammico.display' has no attribute 'explore_analysis'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[12], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mmdisplay\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexplore_analysis\u001b[49m(mydict, identify\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msummary\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
"\u001b[0;31mAttributeError\u001b[0m: module 'ammico.display' has no attribute 'explore_analysis'"
]
}
],
"source": [
"mdisplay.explore_analysis(mydict, identify=\"summary\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Convert the dictionary of dictionarys into a dictionary with lists:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T10:00:56.387360Z",
"iopub.status.busy": "2023-05-05T10:00:56.386744Z",
"iopub.status.idle": "2023-05-05T10:00:56.400976Z",
"shell.execute_reply": "2023-05-05T10:00:56.400092Z"
}
},
"outputs": [],
"source": [
"outdict2 = mutils.append_data_to_dict(mydict)\n",
"df2 = mutils.dump_df(outdict2)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T10:00:56.411671Z",
"iopub.status.busy": "2023-05-05T10:00:56.410625Z",
"iopub.status.idle": "2023-05-05T10:00:56.431836Z",
"shell.execute_reply": "2023-05-05T10:00:56.430851Z"
}
},
"outputs": [
{
"data": {
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>filename</th>\n",
" <th>const_image_summary</th>\n",
" <th>3_non-deterministic summary</th>\n",
" <th>How many persons on the picture?</th>\n",
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" <td>[a man with a medical mask on while looking at...</td>\n",
" <td>1</td>\n",
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"text/plain": [
" filename const_image_summary \n",
"0 data/102141_2_eng.png a collage of images including a corona sign, a... \\\n",
"1 data/106349S_por.png a man wearing a face mask while looking at a c... \n",
"2 data/102730_eng.png two people in blue coats spray disinfection a van \n",
"\n",
" 3_non-deterministic summary \n",
"0 [a collage of pictures with medical equipment,... \\\n",
"1 [a man with a medical mask on while looking at... \n",
"2 [a couple of people in blue coats spray water,... \n",
"\n",
" How many persons on the picture? Are there any politicians in the picture? \n",
"0 1 no \\\n",
"1 1 yes \n",
"2 2 no \n",
"\n",
" Does the picture show something from medicine? \n",
"0 yes \n",
"1 yes \n",
"2 yes "
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df2.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"execution": {
"iopub.execute_input": "2023-05-05T10:00:56.441005Z",
"iopub.status.busy": "2023-05-05T10:00:56.440256Z",
"iopub.status.idle": "2023-05-05T10:00:56.447635Z",
"shell.execute_reply": "2023-05-05T10:00:56.446916Z"
}
},
"outputs": [],
"source": [
"df2.to_csv(\"./data_out2.csv\")"
]
},
{
"cell_type": "code",
"execution_count": null,
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"outputs": [],
"source": []
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