From b9ef52107b81bf043cdd0119c43768a162d07f43 Mon Sep 17 00:00:00 2001
From: Petr Andriushchenko <pitandmind@gmail.com>
Date: Mon, 27 Feb 2023 15:28:26 +0100
Subject: [PATCH] fixed opencv version

---
 misinformation/test/test_summary.py | 30 ++++++++++++++---------------
 pyproject.toml                      |  2 +-
 2 files changed, 15 insertions(+), 17 deletions(-)

diff --git a/misinformation/test/test_summary.py b/misinformation/test/test_summary.py
index fde1045..c2981b9 100644
--- a/misinformation/test/test_summary.py
+++ b/misinformation/test/test_summary.py
@@ -38,14 +38,6 @@ def test_analyse_image():
         id_ = os.path.splitext(os.path.basename(img_path))[0]
         mydict[id_] = {"filename": img_path}
 
-    summary_device = device("cuda" if cuda.is_available() else "cpu")
-    summary_model, summary_vis_processors, _ = load_model_and_preprocess(
-        name="blip_caption",
-        model_type="base_coco",
-        is_eval=True,
-        device=summary_device,
-    )
-
     for key in mydict:
         mydict[key] = sm.SummaryDetector(mydict[key]).analyse_image()
     keys = list(mydict.keys())
@@ -90,6 +82,17 @@ def test_analyse_image():
         "a person running on a beach near a rock formation"
     )
 
+    del sm.SummaryDetector.summary_model, sm.SummaryDetector.summary_vis_processors
+    cuda.empty_cache()
+
+    summary_device = device("cuda" if cuda.is_available() else "cpu")
+    summary_model, summary_vis_processors, _ = load_model_and_preprocess(
+        name="blip_caption",
+        model_type="base_coco",
+        is_eval=True,
+        device=summary_device,
+    )
+
     for key in mydict:
         mydict[key] = sm.SummaryDetector(mydict[key]).analyse_image(
             summary_model, summary_vis_processors
@@ -136,6 +139,9 @@ def test_analyse_image():
         "a person running on a beach near a rock formation"
     )
 
+    del summary_model, summary_vis_processors
+    cuda.empty_cache()
+
     summary_model, summary_vis_processors, _ = load_model_and_preprocess(
         name="blip_caption",
         model_type="large_coco",
@@ -210,14 +216,6 @@ def test_analyse_questions():
         id_ = os.path.splitext(os.path.basename(img_path))[0]
         mydict[id_] = {"filename": img_path}
 
-    summary_device = device("cuda" if cuda.is_available() else "cpu")
-    (
-        summary_VQA_model,
-        summary_VQA_vis_processors,
-        summary_VQA_txt_processors,
-    ) = load_model_and_preprocess(
-        name="blip_vqa", model_type="vqav2", is_eval=True, device=summary_device
-    )
     list_of_questions = [
         "How many persons on the picture?",
         "What happends on the picture?",
diff --git a/pyproject.toml b/pyproject.toml
index 65f5b43..b138efe 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -40,7 +40,7 @@ dependencies = [
     "pytest-cov",
     "matplotlib",
     "pytest",
-    "opencv-contrib-python",
+    "opencv-contrib-python <= 4.6",
     "googletrans==3.1.0a0",
     "spacy",
     "jupyterlab",