FLUX.1 [dev] with Controlnets and Loras · Differential Diffusion
통합
flux-general/differential-diffusion
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/flux-general/differential-diffusion?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/flux-general/differential-diffusion?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/flux-general/differential-diffusion", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/ko/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.com/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "flux-general/differential-diffusion",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
}
Doitong API를 통해 FLUX.1 [dev] with Controlnets and Loras · Differential Diffusion 모델(flux-general/differential-diffusion)을 호출합니다. 에이전트용 문서: https://doitong.com/ko/developers/models/flux-general/differential-diffusion.md
POST https://api.doitong.com/v1/run/flux-general/differential-diffusion?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
응답 상태가 "queued" 또는 "running"이면 "succeeded"가 될 때까지 GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20을 폴링하세요. 파일은 outputs[].url에 있습니다. POST https://api.doitong.com/v1/quote/flux-general/differential-diffusion에 동일한 본문을 보내면 실행 전에 정확한 가격을 반환합니다.
이 요청: ≈$0.138 138 API 크레딧 이 페이지에서 실행
새 API 키입니다. 지금만 표시되며 이미 아래 코드와 API 키 필드에 입력되어 있습니다. 안전하게 보관하세요. 브라우저에서 실행되는 코드에 절대 넣지 마세요.
Doitong에서 제작됨
Doitong 커뮤니티가 FLUX.1 [dev] with Controlnets and Loras로 만든 공개 작품입니다. 한 번의 클릭으로 프롬프트를 재사용하세요.
Close-up portrait seorang wanita berkulit pucat berdiri setengah tubuh di dalam air berwarna lembut kebiruan, dikelilingi bunga teratai berkelopak penuh yang bermekaran indah di permukaan air. Rambutnya pirang pucat tersanggul longgar dengan beberapa helaian tipis jatuh alami membingkai sisi...
Close-up portrait seorang wanita berkulit pucat berdiri setengah tubuh di dalam air berwarna lembut kebiruan, dikelilingi bunga teratai berkelopak penuh yang bermekaran indah di permukaan air. Rambutnya pirang pucat tersanggul longgar dengan beberapa helaian tipis jatuh alami membingkai sisi...
Prompt Details Seorang wanita berkulit pucat berdiri setengah tubuh di dalam air berwarna lembut kebiruan, dikelilingi bunga teratai berkelopak penuh yang bermekaran indah di permukaan air. Rambutnya pirang pucat tersanggul longgar dengan beberapa helaian tipis jatuh alami membingkai sisi...
Seorang wanita berkulit pucat berdiri setengah tubuh di dalam air berwarna lembut kebiruan, dikelilingi bunga teratai berkelopak penuh yang bermekaran indah di permukaan air. Rambutnya pirang pucat tersanggul longgar dengan beberapa helaian tipis jatuh alami membingkai sisi wajahnya. Ia memeluk...
"Potret sinematik ultra-realistis close-up seorang anak laki-laki kecil (balita) yang sangat menggemaskan dengan mata cokelat besar yang ekspresif, rambut hitam berantakan yang tebal, mengenakan kaus putih kerah henley. Dia berpose dengan kedua tangan terkatup di depan dada, menunjukkan senyum...
"Potret sinematik ultra-realistis close-up seorang anak laki-laki kecil (balita) yang sangat menggemaskan dengan mata cokelat besar yang ekspresif, rambut hitam berantakan yang tebal, mengenakan kaus putih kerah henley. Dia berpose dengan kedua tangan terkatup di depan dada, menunjukkan senyum...
"Potret sinematik ultra-realistis close-up seorang anak laki-laki kecil (balita) yang sangat menggemaskan dengan mata cokelat besar yang ekspresif, rambut hitam berantakan yang tebal, mengenakan kaus putih kerah henley. Dia berpose dengan kedua tangan terkatup di depan dada, menunjukkan senyum...
Foto sinematik hiper-realistis resolusi tinggi menampilkan seorang pria muda Indonesia dengan tubuh ramping dan proporsional, rambut hitam pendek agak acak, mengenakan jaket kulit hitam, celana riding fit, dan sepatu motor. Ia sedang melakukan aksi freestyle ekstrem dengan motor sport 500cc...
Foto sinematik hiper-realistis resolusi tinggi menampilkan seorang pria muda Indonesia dengan tubuh ramping dan proporsional, rambut hitam pendek agak acak, mengenakan jaket kulit hitam dan celana riding fit. Ia sedang bersiap melakukan freestyle menggunakan motor sport 500cc berwarna merah,...
요청 만들기
컨트롤은 모델 스키마에서 생성됩니다. 값을 변경하면 코드와 가격이 업데이트됩니다.
/run/flux-general/differential-diffusion?wait=20
견적 → $0.138
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/flux-general/differential-diffusion?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/flux-general/differential-diffusion?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/flux-general/differential-diffusion", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "run",
"arguments": {
"model_id": "flux-general/differential-diffusion",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"wait_seconds": 20
}
}
}
FLUX.1 [dev] with Controlnets and Loras · Differential Diffusion 정보
변경 맵 이미지로 각 영역의 수정 정도를 제어해 소스 이미지를 영역별로 변환합니다. `prompt`, `image_url`, `change_map_image_url`이 필요합니다. LoRA, ControlNet, IP-Adapter 및 참조 이미지도 지원합니다. `num_inference_steps`는 1~50, `num_images`는 최대 10이며 png 또는 jpeg로 출력합니다.
매개변수
표준 이름이나 네이티브 이름 중 하나만 보내세요. 표준 이름
prompt필수
image_size선택 사항
num_inference_steps선택 사항
seed선택 사항
loras선택 사항
loras[].path필수
loras[].scale선택 사항
control_loras선택 사항
control_loras[].path필수
control_loras[].scale선택 사항
control_loras[].control_image_url필수
control_loras[].preprocess선택 사항
controlnets선택 사항
controlnets[].path필수
controlnets[].config_url선택 사항
controlnets[].variant선택 사항
controlnets[].control_image_url필수
controlnets[].mask_image_url선택 사항
controlnets[].mask_threshold선택 사항
controlnets[].conditioning_scale선택 사항
controlnets[].start_percentage선택 사항
controlnets[].end_percentage선택 사항
controlnet_unions선택 사항
controlnet_unions[].path필수
controlnet_unions[].config_url선택 사항
controlnet_unions[].variant선택 사항
controlnet_unions[].controls필수
controlnet_unions[].controls[].control_image_url필수
controlnet_unions[].controls[].mask_image_url선택 사항
controlnet_unions[].controls[].control_mode필수
controlnet_unions[].controls[].conditioning_scale선택 사항
controlnet_unions[].controls[].mask_threshold선택 사항
controlnet_unions[].controls[].start_percentage선택 사항
controlnet_unions[].controls[].end_percentage선택 사항
ip_adapters선택 사항
ip_adapters[].path필수
ip_adapters[].subfolder선택 사항
ip_adapters[].weight_name선택 사항
ip_adapters[].image_encoder_path필수
ip_adapters[].image_encoder_subfolder선택 사항
ip_adapters[].image_encoder_weight_name선택 사항
ip_adapters[].image_url필수
ip_adapters[].mask_image_url선택 사항
ip_adapters[].mask_threshold선택 사항
ip_adapters[].scale필수
easycontrols선택 사항
easycontrols[].control_method_url필수
easycontrols[].scale선택 사항
easycontrols[].image_url필수
easycontrols[].image_control_type필수
fill_image선택 사항
fill_image.fill_image_url선택 사항
guidance_scale선택 사항
real_cfg_scale선택 사항
use_real_cfg선택 사항
use_cfg_zero선택 사항
num_images선택 사항
num_outputs
enable_safety_checker선택 사항
reference_image_url선택 사항
reference_strength선택 사항
reference_start선택 사항
reference_end선택 사항
base_shift선택 사항
max_shift선택 사항
output_format선택 사항
use_beta_schedule선택 사항
sigma_schedule선택 사항
scheduler선택 사항
negative_prompt선택 사항
nag_scale선택 사항
nag_tau선택 사항
nag_alpha선택 사항
nag_end선택 사항
image_url필수
image
change_map_image_url필수
strength선택 사항
파일 매개변수에는 공개 https:// URL, 최대 10 MB의 data: URI 또는 업로드의 file_url을 사용할 수 있습니다. 파일
출력
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "flux-general/differential-diffusion",
"status": "succeeded",
"created_at": "2026-10-20T12:00:00Z",
"started_at": "2026-10-20T12:00:02Z",
"completed_at": "2026-10-20T12:00:09Z",
"queue_position": null,
"cost": {
"credits": 138,
"usd": "0.138",
"charged": 138,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"change_map_image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"output": {
"images": [
{
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"width": 1024,
"height": 768,
"content_type": "image/jpeg"
}
],
"timings": {},
"seed": 42,
"has_nsfw_concepts": [
false
],
"prompt": "string"
},
"outputs": [
{
"type": "image",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"width": 1024,
"height": 768,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
출력 필드
- images
- array of object {url, width, height, content_type}생성된 이미지의 파일 정보입니다.
- timings
- object
- seed
- integer이미지 생성 시드입니다. 입력에서 시드를 생략하면 무작위로 선택된 값이 포함되고, 그렇지 않으면 제공한 값이 반복됩니다.
- has_nsfw_concepts
- array of boolean생성된 이미지에 NSFW 개념이 나타나는지 나타냅니다.
- prompt
- string이미지 생성에 사용되는 프롬프트입니다.
다른 FLUX.1 [dev] with Controlnets and Loras 변형
더 많은 모델: 이미지 편집
AI 에이전트용: 이 페이지의 Markdown 버전: https://doitong.com/ko/developers/models/flux-general/differential-diffusion.md. 모든 모델 및 가이드: https://doitong.com/developers/llms.txt






