Support for more image types on upload

requirements.txt

@@ -6,6 +6,7 @@ matplotlib
 numpy>=1.18.5
 opencv-python-headless==4.10.0.84
 Pillow>=7.1.2
+pillow-heif>=0.18.0
 python-dateutil
 python-dotenv
 requests

roboflow/__init__.py

@@ -15,7 +15,7 @@
 from roboflow.models import CLIPModel, GazeModel  # noqa: F401
 from roboflow.util.general import write_line
 
-__version__ = "1.1.57"
+__version__ = "1.1.58"
 
 
 def check_key(api_key, model, notebook, num_retries=0):

roboflow/core/project.py

@@ -22,6 +22,9 @@
     "image/jpeg",
     "image/png",
     "image/webp",
+    "image/tiff",
+    "image/avif",
+    "image/heic",
 }
 
 

roboflow/util/folderparser.py

@@ -7,7 +7,7 @@
 
 from .image_utils import load_labelmap
 
-IMAGE_EXTENSIONS = {".jpg", ".jpeg", ".png", ".bmp"}
+IMAGE_EXTENSIONS = {".jpg", ".jpeg", ".png", ".bmp", ".tiff", ".tif", ".avif", ".heic"}
 ANNOTATION_EXTENSIONS = {".txt", ".json", ".xml", ".csv", ".jsonl"}
 LABELMAPS_EXTENSIONS = {".labels", ".yaml", ".yml"}
 

roboflow/util/image_utils.py

@@ -1,12 +1,18 @@
+# Standard library imports
 import base64
 import io
 import os
 import urllib
 
+# Third-party imports
+import pillow_heif  # type: ignore[import-untyped]
 import requests
 import yaml
 from PIL import Image
 
+pillow_heif.register_heif_opener(thumbnails=False)  # Register for HEIF/HEIC
+pillow_heif.register_avif_opener(thumbnails=False)  # Register for AVIF
+
 
 def check_image_path(image_path):
     """
@@ -74,9 +80,18 @@ def validate_image_path(image_path):
 def file2jpeg(image_path):
     import cv2
 
+    # OpenCV will handle standard formats efficiently
     img = cv2.imread(image_path)
-    image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
-    pilImage = Image.fromarray(image)
+    if img is not None:
+        # Convert BGR to RGB for PIL
+        image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+        pilImage = Image.fromarray(image)
+    else:
+        # If OpenCV fails, the format might be HEIC/AVIF which are handled by PIL
+        pilImage = Image.open(image_path)
+        if pilImage.mode != "RGB":
+            pilImage = pilImage.convert("RGB")
+
     buffered = io.BytesIO()
     pilImage.save(buffered, quality=100, format="JPEG")
     return buffered.getvalue()

tests/test_project.py

@@ -15,6 +15,8 @@ def test_check_valid_image_with_accepted_formats(self):
             "rabbit2.jpg",
             "hand-rabbit.PNG",
             "woodland-rabbit.png",
+            "file_example_TIFF_1MB.tiff",
+            "sky-rabbit.heic",
         ]
 
         for image in images_to_test:
@@ -23,7 +25,6 @@ def test_check_valid_image_with_accepted_formats(self):
     def test_check_valid_image_with_unaccepted_formats(self):
         images_to_test = [
             "sky-rabbit.gif",
-            "sky-rabbit.heic",
         ]
 
         for image in images_to_test:
@@ -32,7 +33,7 @@ def test_check_valid_image_with_unaccepted_formats(self):
     def test_upload_raises_upload_image_error(self):
         responses.add(
             responses.POST,
-            f"{API_URL}/dataset/{PROJECT_NAME}/upload?api_key={ROBOFLOW_API_KEY}" f"&batch={DEFAULT_BATCH_NAME}",
+            f"{API_URL}/dataset/{PROJECT_NAME}/upload?api_key={ROBOFLOW_API_KEY}&batch={DEFAULT_BATCH_NAME}",
             json={
                 "error": {
                     "message": "Invalid image.",
@@ -58,15 +59,15 @@ def test_upload_raises_upload_annotation_error(self):
         # Image upload
         responses.add(
             responses.POST,
-            f"{API_URL}/dataset/{PROJECT_NAME}/upload?api_key={ROBOFLOW_API_KEY}" f"&batch={DEFAULT_BATCH_NAME}",
+            f"{API_URL}/dataset/{PROJECT_NAME}/upload?api_key={ROBOFLOW_API_KEY}&batch={DEFAULT_BATCH_NAME}",
             json={"success": True, "id": image_id},
             status=200,
         )
 
         # Annotation
         responses.add(
             responses.POST,
-            f"{API_URL}/dataset/{PROJECT_NAME}/annotate/{image_id}?api_key={ROBOFLOW_API_KEY}" f"&name={image_name}",
+            f"{API_URL}/dataset/{PROJECT_NAME}/annotate/{image_id}?api_key={ROBOFLOW_API_KEY}&name={image_name}",
             json={
                 "error": {
                     "message": "Image was already annotated.",