Let CraterView.ai restore and enhance your images

# 1 — ask for somewhere to put the file
LEN=$(wc -c < image.jpg)
curl -X POST "https://api.craterview.ai/v1/uploads" \
  -H "Authorization: Bearer $CV_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{\"content_type\": \"image/jpeg\", \"content_length\": $LEN}"
# -> {"upload_url": "...", "input_key": "..."}

# 2 — upload the bytes straight to storage. The content type is signed,
#     so it has to match what step 1 was told.
curl -X PUT "$UPLOAD_URL" \
  -H "Content-Type: image/jpeg" \
  --data-binary @image.jpg

# 3 — submit, and wait for a fast job in the same response
curl -X POST "https://api.craterview.ai/v1/jobs?wait=30" \
  -H "Authorization: Bearer $CV_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{\"model\": \"echo\", \"input_key\": \"$INPUT_KEY\",
       \"params\": {\"scale\": 2}}"
# echo is free, for building against. When you are ready, swap in
# cv-enhance-v3 to enlarge, cv-restore-v1 to repair,
# or cv-headshot-v1 for portraits.

# pip install craterview
from craterview import CraterView

# a client, once
cv = CraterView(api_key="cv_...", base_url="https://api.craterview.ai")

# steps 1, 2 and 3 in a single call
job = cv.run(
    # echo is free, for building against. Swap in a paid model when ready:
    # cv-enhance-v3 to enlarge, cv-restore-v1 to repair,
    # cv-headshot-v1 for portraits.
    "image.jpg", model="echo",
    scale=2, wait=30,
)

job.save("image-restored.jpg")

// npm install craterview
// TypeScript source: bundle it, or run it with tsx
import { CraterView } from "craterview";

// a client, once
const cv = new CraterView({ apiKey: "cv_...", baseUrl: "https://api.craterview.ai" });

// steps 1, 2 and 3 in a single call
const job = await cv.run(file, {
  // echo is free, for building against. Swap in a paid model when ready:
  // cv-enhance-v3 to enlarge, cv-restore-v1 to repair,
  // cv-headshot-v1 for portraits.
  model: "echo",
  scale: 2, wait: 30,
});

const blob = await job.blob();