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fix: VLM décrit TOUJOURS l'ancre à la capture, pas seulement si OCR échoue
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L'OCR seul donnait du bruit (\"- C\", \"emo\"). Le VLM (qwen2.5vl:3b)
est maintenant appelé systématiquement pour décrire l'ancre en 5 mots
(\"folder icon named Demo\", \"search bar with magnifier icon\").

Le target_text utilise l'OCR si lisible, sinon la description VLM.
La description VLM est toujours stockée dans ocr_description.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Dom
2026-04-22 15:30:19 +02:00
parent 4ce9c47f45
commit f04398d5a7
1 changed files with 43 additions and 32 deletions
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39
visual_workflow_builder/backend/api_v3/capture.py
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@@ -210,19 +210,18 @@ def select_anchor():
target_text = ""
ocr_description = ""
try:
# 1. OCR du crop (rapide, pour le texte visible)
from services.ocr_service import ocr_extract_text
target_text = ocr_extract_text(expanded).strip()
if not target_text:
target_text = ocr_extract_text(thumbnail).strip()
print(f"🔍 [OCR] Texte extrait de l'ancre: '{target_text}'")
ocr_text = ocr_extract_text(expanded).strip()
if not ocr_text:
ocr_text = ocr_extract_text(thumbnail).strip()
print(f"🔍 [OCR] Texte brut: '{ocr_text}'")
# Si le texte OCR est trop court ou vide, décrire via VLM
if len(target_text) < 3:
# 2. VLM décrit TOUJOURS l'ancre (comprend icône + contexte)
try:
import requests as http_requests
ollama_url = os.environ.get("OLLAMA_URL", "http://localhost:11434")
# Encoder le crop en base64 pour le VLM
thumb_buffer = BytesIO()
thumbnail.save(thumb_buffer, format='PNG')
thumb_b64 = base64.b64encode(thumb_buffer.getvalue()).decode('utf-8')
@@ -231,21 +230,33 @@ def select_anchor():
f"{ollama_url}/api/generate",
json={
"model": "qwen2.5vl:3b",
"prompt": "Describe this UI element in 5 words. Just the name, nothing else.",
"prompt": "Describe this UI element in 5 words maximum. Include the exact text visible. Example: 'folder icon named Demo' or 'Save button' or 'search bar with magnifier icon'. Just the description, nothing else.",
"images": [thumb_b64],
"stream": False,
"options": {"temperature": 0.1, "num_predict": 15}
"options": {"temperature": 0.1, "num_predict": 20}
},
timeout=60
)
if resp.status_code == 200:
ocr_description = resp.json().get("response", "").strip()
print(f"🏷️ [VLM] Description ancre: '{ocr_description}'")
vlm_desc = resp.json().get("response", "").strip().strip('"').strip("'")
print(f"🏷️ [VLM] Description ancre: '{vlm_desc}'")
if vlm_desc and len(vlm_desc) > 2:
ocr_description = vlm_desc
# Si l'OCR a donné du bruit, utiliser la description VLM comme target
if len(ocr_text) < 3 or ocr_text in ('- -', '- C', '--'):
target_text = vlm_desc
else:
target_text = ocr_text
else:
target_text = ocr_text
ocr_description = ocr_text
else:
target_text = ocr_text
ocr_description = ocr_text
except Exception as vlm_err:
print(f"⚠️ [VLM] Description ancre échouée: {vlm_err}")
else:
# Le texte OCR est suffisant, l'utiliser aussi comme description
ocr_description = target_text
target_text = ocr_text
ocr_description = ocr_text
except ImportError:
print("⚠️ [OCR] docTR non disponible, analyse ancre ignorée")
except Exception as ocr_err: