deepfaketar / python /qloraprep2.py
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import os
import json
import sys
import uuid
# modifications = [
# "There is a modification involving the addition of a beard. ",
# "There is a modification involving the addition of a pair of eyeglasses. ",
# "There is a modification making the person to appear to be smiling. ",
# "There is a modification making the person to appear younger than they really are. ",
# "There is a modification involving the addition of Bangs. "
# "There is no modification. "
# ]
modifications = [
"eye. ",
"eyebrow. ",
"hair. ",
"nose. ",
"lip. "
]
# Function to get list of image files in the directory
def get_image_files(directory):
image_files = []
for filename in os.listdir(directory):
if filename.endswith(".jpg") or filename.endswith(".png"):
image_files.append(filename)
return image_files
def get_idx(string):
#print(string)
deepfakes = [
"eye",
"eyebrow",
"hair",
"nose",
"lip",
]
for i in range(len(deepfakes)):
if (deepfakes[i]==string):
return i
#returns correct string
def get_answer(directory):
tag = directory[32:len(directory)-1]
print(tag)
#print(tag)
ans=[]
count = 0
while (len(tag)>0):
count+=1
if (count>5): break
x=tag.find('-')
#print(x)
if (x==-1):
ans.append(get_idx(tag))
break
str=tag[0:x]
tag=tag[x+1:]
ans.append(get_idx(str))
#print(ans)
return ans
# Function to create JSON file with entries for each image file
def create_json(image_dir, json_file_path):
# Get list of image files
image_files = get_image_files(image_dir)
# Create list of entries for each image file
image_entries = []
with open(json_file_path, "r") as json_file:
image_entries=json.load(json_file)
# print(len(image_entries))
# print(image_dir)
answer=""
bruh = get_answer(image_dir)
# print(bruh)
# for i in range(len(bruh)-1):
# answer=answer+str(i+1)+"-"
# answer=answer+str(bruh[-1]+1)+". "
for i in bruh:
answer=answer+modifications[i]
for image_file in image_files:
image_path = os.path.join(image_dir, image_file)
entry_id = str(uuid.uuid4())
entry = {
"id": entry_id,
"image": image_path,
"conversations": [
{
"from": "human",
"value": "This image could possibly have deepfake modifications made to it." + " ".join(modifications) + "Thus your job is to figure out all the modifications. Extraneous guesses will be penalized. There is a chance that no modifications were made."
},
{
"from": "gpt",
"value": answer
}
]
}
image_entries.append(entry)
# Writing data to the JSON file
with open(json_file_path, "w") as json_file:
json.dump(image_entries, json_file, indent=4)
print("JSON file created successfully at", json_file_path)
# Check if the script is called with the correct number of arguments
if len(sys.argv) != 3:
print("Usage: python script.py <image_directory> <json_output_file>")
sys.exit(1)
# Get command-line arguments
image_dir = sys.argv[1] #directory path
json_file_path = sys.argv[2] #output path
# Check if the specified directory exists
if not os.path.isdir(image_dir):
print("Error: The specified directory does not exist.")
sys.exit(1)
# Call the function to create the JSON file
#print(image_dir)
#get_answer(image_dir)
create_json(image_dir, json_file_path)