76 lines
9.8 KiB
Plaintext
76 lines
9.8 KiB
Plaintext
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„ Z e d krfe ƒ dS ) u_
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AI Image Classification Pipeline
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Maps images → IOM objects + defect codes + reality signals
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©Úself© r úC/home/bernt/.openclaw/workspace/iom/ai_pipeline/image_classifier.pyÚto_dict s
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úzImageAnalysis.to_dictN)
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e d œd d „Zd S )"ÚImageClassifierz.Classifies images into IOM objects and signalsc C s" | ¡ | _| ¡ | _| ¡ | _d S ©N)Ú_load_object_patternsZobject_patternsÚ_load_defect_patternsZdefect_patternsÚ_load_scene_classifiersÚscene_classifiersr r r r Ú__init__# s
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g d¢ddœdg d¢ddœdg d¢ddœdg d¢ddœdœS )z Load object detection patternsú BYG-FAC-WIN)ÚwindowZglassÚframeZglazingçffffffæ?)Ú goid_prefixÚkeywordsZconfidence_thresholdú TRN-ROD-SUR)ÚroadZpavementZasphaltZconcreteÚsurfacegš™™™™™é?z BEL-STR-LIG)ÚlightZlampZpoleZ illuminationç è?z COM-DIS-SGN)ÚsignZ billboardZposterÚdisplayz ENE-EVC-CHA)ZchargerÚevZelectricÚcharging_stationú BYG-FAC-WAL)ZwallÚfacadeÚbuildingZexteriorúTRN-VEH)ÚcarÚtruckZbusÚvehicleZpickupç333333ë?zHUM-PED)ZpersonÚ
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œS )z Load defect detection patterns)ÚrustÚ corrosionÚ oxidationZ brown_stainr )r+ Úseverity)ÚdirtÚgrimeÚstainZ pollutionÚdust)ÚcrackÚchipÚscratchÚdamageÚwearé )ÚgraffitiÚtagÚpaintÚ vandalism)ÚmissingÚabsentZ
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broken_offÚdetachedé )ÚbrokenÚdamagedÚ fracturedZ destroyed)ÚblockedÚ
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¢g d¢dœdœS )z"Load scene classification patterns)r- Úsidewalkr7 Ústreet)Ú walkabilityÚ noise_levelÚ heat_stress)r+ Úsignals)Ú constructionZcraneZscaffoldr7 Zconstruction_completionZtemporary_structure_density)ÚshopZ
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restaurantr1 r> )Z public_lifeZinformal_economyZstreet_food_density)ZhouseZ apartmentÚ residentialÚhome)Úfamily_presenceZ rent_burdenZcommunity_activity)ÚfactoryZ warehouseÚ
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odor_indexro Z air_quality)ÚparkÚtreeZgrassÚgreen)Z shade_indexrp rv )Ú urban_streetÚconstruction_siteÚcommercial_areart rx Ú
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image_pathÚlocationÚmetadatar c
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C sn | |¡}| ||¡}| |¡}| |||¡}tdd„ |D ƒƒtt|ƒdƒ }| ||¡} t|||||| d�S )zÓ
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Analyze an image and extract IOM objects, defects, and signals
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In production, this would use actual AI models (YOLO, CLIP, etc.)
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For now, simulate with pattern matching
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c s s | ]}| d d¡V qdS )r r N©Úget©Ú.0Úobjr r r Ú <genexpr>ª ó z0ImageClassifier.analyze_image.<locals>.<genexpr>é r ) Ú_simulate_object_detectionÚ_simulate_defect_detectionÚ_classify_sceneÚ_extract_signalsÚsumÚmaxÚlenÚ_extract_urban_contextr )
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