Added image recognition

code/vision_processing.py

@@ -0,0 +1,46 @@
+import io
+import os
+import asyncio
+from config import debug
+# Imports the Google Cloud client library
+from google.cloud import vision
+
+# Instantiates a client
+client = vision.ImageAnnotatorClient()
+
+async def process(attachment):
+    debug("Processing image...")
+    image = vision.Image()
+    image.source.image_uri = attachment.url
+    labels = client.label_detection(image=image)
+    texts = client.text_detection(image=image)
+    objects = client.object_localization(image=image)
+    labels = labels.label_annotations
+    texts = texts.text_annotations
+    objects = objects.localized_object_annotations
+    #we take the first 4 labels and the first 4 objects
+    labels = labels[:2]
+    objects = objects[:7]
+    final = "<image\n"
+    if len(labels) > 0: final += "Labels:\n"
+    for label in labels:
+        final += label.description + ", "
+    final = final[:-2] + "\n"
+    if len(texts) > 0: final += "Text:\n"
+    try: final += texts[0].description + "\n" #we take the first text, wich is the whole text in reality
+    except: pass
+    if len(objects) > 0: final += "Objects:\n"
+    for obj in objects:
+        final += obj.name + ", "
+    final = final[:-2] + "\n"
+    final += "!image>"
+    # we store the result in a file called attachment.key.txt in the folder ./../database/google-vision/results
+    # we create the folder if it doesn't exist
+    if not os.path.exists("./../database/google-vision/results"):
+        os.mkdir("./../database/google-vision/results")
+    # we create the file
+    with open(f"./../database/google-vision/results/{attachment.id}.txt", "w", encoding="utf-8") as f:
+        f.write(final)
+        f.close()
+
+    return final